Posts on KnightLi Blog

PersonaPlex Quick Guide: Full-Duplex Conversational Speech with Persona and Voice Control

Fri, 10 Apr 2026 11:34:38 +0800

PersonaPlex is a real-time full-duplex speech-to-speech conversational model. It provides two key control dimensions:

text prompts for role/persona control
audio conditioning for voice style control

It is built on Moshi architecture and weights, aiming for low-latency and more natural spoken interactions with consistent persona behavior.

What It Is Good For

Common use cases include:

real-time voice assistants
customer-service style role interactions
low-latency conversational demos
persona + voice control experiments

Prerequisites

Install the Opus audio codec development library:

# Ubuntu/Debian
sudo apt install libopus-dev

# Fedora/RHEL
sudo dnf install opus-devel

Installation and Environment

Install from repository:

`1`	`pip install moshi/.`

For Blackwell GPUs, an extra step can be used:

`1`	`pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu130`

After accepting the PersonaPlex model license on Hugging Face, set your token:

`1`	`export HF_TOKEN=<YOUR_HUGGINGFACE_TOKEN>`

Launch Live Server

Standard launch (temporary SSL):

`1`	`SSL_DIR=$(mktemp -d); python -m moshi.server --ssl "$SSL_DIR"`

If GPU memory is limited, enable CPU offload (accelerate required):

1
2

pip install accelerate
SSL_DIR=$(mktemp -d); python -m moshi.server --ssl "$SSL_DIR" --cpu-offload

Use localhost:8998 for local runs, or the printed access link for remote setups.

Offline Evaluation

The offline script consumes an input wav and produces an output wav with the same duration:

HF_TOKEN=<TOKEN> \
python -m moshi.offline \
  --voice-prompt "NATF2.pt" \
  --input-wav "assets/test/input_assistant.wav" \
  --seed 42424242 \
  --output-wav "output.wav" \
  --output-text "output.json"

HF_TOKEN=<TOKEN> \
python -m moshi.offline \
  --voice-prompt "NATM1.pt" \
  --text-prompt "$(cat assets/test/prompt_service.txt)" \
  --input-wav "assets/test/input_service.wav" \
  --seed 42424242 \
  --output-wav "output.wav" \
  --output-text "output.json"

Built-in Voice Labels

Natural(female): NATF0, NATF1, NATF2, NATF3
Natural(male): NATM0, NATM1, NATM2, NATM3
Variety(female): VARF0, VARF1, VARF2, VARF3, VARF4
Variety(male): VARM0, VARM1, VARM2, VARM3, VARM4

Prompting Tips

Training coverage mainly includes:

Assistant Role
Customer Service Roles
Casual Conversations

Practical tips:

define role identity first, then add task context
keep prompts concise to reduce persona drift
reuse the same voice prompt for stable comparisons

Summary

PersonaPlex stands out not because it gives one smarter answer, but because it keeps persona and voice behavior more consistent in real-time speech interaction.

For full-duplex voice agents, this is a practical option worth testing and benchmarking.

Anthropic's Harness Direction: Agent Infrastructure Is Becoming an Agent OS

Fri, 10 Apr 2026 09:22:56 +0800

Anthropic recently published an engineering write-up on Harness. On the surface, it explains product implementation. At a deeper level, it answers a longer-term question:

As model capabilities keep evolving, which layers in an Agent system should stay stable, and which should remain fast to replace?

Core Judgment

My key takeaway is: Agent infrastructure is becoming more like a lightweight Agent OS.

The focus is not to hard-code today’s best workflow, but to define long-lived system abstractions.

Why This Matters

Common problems in many Agent frameworks include:

turning temporary model limitations into permanent architecture
treating prompt engineering as a system boundary
turning one useful patch into a long-term dependency

Models will keep improving. A patch that is reasonable today may become technical debt tomorrow.

Anthropic’s Approach: From Concrete Harness to Meta-Harness

Instead of committing to one fixed orchestration style, this approach abstracts three stable interfaces:

session: recoverable event and state history
harness: reasoning and orchestration loop (brain)
sandbox: execution environment and tool capabilities (hands)

After separation, the system becomes easier to replace, recover, and scale.

1) Session Is Not the Context Window

A critical point is: Session is not model context.

Session should be a queryable, replayable, and recoverable event log, not a direct history dump into the model.

Benefits of this design:

trimming does not mean history disappears
compaction does not mean facts are lost
crash recovery can return to the event layer instead of relying on summary memory

2) Harness as a Replaceable Orchestration Layer

Harness should focus on orchestration rather than holding business state.

An ideal interface is closer to:

execute(name, input) -> string

This means the model only needs to know what capabilities it can call, without being tightly bound to specific devices, containers, or operating systems.

3) Sandbox Is the “Hands,” Not the “Brain”

When brain and hands are decoupled:

tool environments can evolve independently
different infrastructure can be integrated in parallel
not every session needs a fully prewarmed execution environment

This directly improves startup and scalability behavior.

Performance and Security Insights

This split often improves both performance and security.

On performance:

start the brain first, then provision hands on demand
reduce Time To First Token (TTFT)

On security:

do not expose high-value credentials directly to the model
use controlled proxy/vault paths for indirect credential access
build security boundaries on system constraints, not on assumptions that “the model probably can’t do this”

OpenClaw and Agent Harness: Why It Looks Like AGI

Fri, 10 Apr 2026 09:16:17 +0800

When many people first try OpenClaw, it feels more like a teammate who can get work done than a chatbot.

That feeling is not mysterious. The key is this: OpenClaw is not a jump in one model capability; it is a complete Agent Harness.

Core Conclusion

The essence of OpenClaw can be summarized as:

the model handles understanding and decisions
the harness handles memory, tools, triggers, execution, and outputs
the two collaborate through a loop to create continuous action

So the core reason it “feels like AGI” is not that the model suddenly became all-powerful, but that systems engineering amplifies what the model can execute.

What Is a Harness

You can think of a harness as an exoskeleton for the model.

A standalone LLM usually provides an answer in a single request. A harness adds these capabilities:

session and state management: link multi-turn tasks
memory mechanisms: store and retrieve context when needed
tool system: call browsers, terminals, files, and external APIs
trigger mechanisms: wake on timers or events instead of waiting for a human prompt every time
output channels: write results back to systems, not just return a paragraph

When these capabilities are connected in one loop, the model shifts from a responder to an executor.

Why OpenClaw Feels Different

A traditional chatbot is “ask once, answer once”.

OpenClaw is more like a closed loop of “observe -> use tools -> inspect results -> decide next”. Once this loop is established, the system can keep moving a task forward.

This is also the most valuable lesson from OpenClaw:

it proves the agent experience mainly comes from architecture design
it decomposes “autonomy” into modules that can be engineered

Value and Boundaries

OpenClaw is general and flexible, but the trade-offs are also clear:

the more context and tool definitions you include, the higher the cost
the more general the system is, the more complex debugging and governance become

In production scenarios, many teams choose smaller, more specialized agents instead of one universal agent.

Sharing an Agent Skill for E-commerce Product Image Cutout and Standardization

Thu, 09 Apr 2026 21:43:50 +0800

product-cutout-normalize is an Agent Skill for product images.

It turns raw product photos into square transparent images with a consistent layout. The default rules are:

a 1024x1024 canvas
transparent background
preserve the full subject as much as possible
rotate vertical subjects to horizontal
center the subject
normalize visible subject width to 820px

It is a good fit for e-commerce assets, product libraries, and product detail page image preparation.

What this skill solves

Even after a basic cutout, product images often still have issues such as:

leftover white or light gray edges
inconsistent subject orientation
inconsistent canvas size
inconsistent subject scale
small specks in transparent regions

This skill handles them with a fixed workflow:

Use Gemini for cutout
Clean light-colored background from the borders
Remove small noise fragments
Rotate vertical images to horizontal
Scale the subject to a target width
Place it in the center of a transparent square canvas

That makes the output cleaner and more suitable for batch use.

When to use it

This is a good fit when you need to:

batch-process product photos
export transparent PNG assets
keep a consistent visual size
use a stable and repeatable workflow

If you only edit a few images or need to manually adjust each layout, this may not be the right tool.

Quick start

The most direct way to run it is:

`1`	`& ".\.venv\Scripts\python.exe" ".codex\skills\product-cutout-normalize\scripts\run_pipeline.py" "input_dir" "output_dir" --overwrite`

Before running it, make sure you have:

GEMINI_API_KEY
google-genai
Pillow

Install dependencies:

`1`	`.\.venv\Scripts\python.exe -m pip install google-genai pillow`

Set the environment variable:

`1`	`$env:GEMINI_API_KEY="your_api_key"`

Output rules

The default output is:

transparent-background PNG
1024x1024 canvas
820px subject width
centered subject
small noise fragments removed

So this is more than a simple background-removal script. It is closer to a product image cleanup script.

Main parameters

Common flags:

--model Default: gemini-2.5-flash-image
--canvas-size Output square canvas size, default 1024
--target-width Visible subject width, default 820
--min-component-pixels Transparent fragments smaller than this are removed, default 500
--overwrite Overwrite existing outputs

For example:

`1`	`& ".\.venv\Scripts\python.exe" ".codex\skills\product-cutout-normalize\scripts\run_pipeline.py" ".\input" ".\output" --canvas-size 1280 --target-width 960 --overwrite`

Workflow

The workflow is straightforward:

Use Gemini for cutout
Clean light-colored border background
Remove small fragments
Rotate vertical images to horizontal
Scale to the target width
Place the result on a transparent square canvas

How it differs from a basic cutout script

Compared with a basic background-removal script, it also handles:

subject orientation normalization
subject size normalization
canvas size normalization
small-fragment cleanup
outputs that are easier to place directly into an asset library

SKILL.md source

The full SKILL.md source is preserved below without modification:

---
name: product-cutout-normalize
description: Run a reusable Gemini product-image pipeline that removes backgrounds, preserves the full subject, rotates tall products to a horizontal orientation, centers them on a 1024x1024 transparent canvas, and normalizes the visible subject width to 820px. Use when the user wants a repeatable cutout-and-normalize workflow for product photos or asks to batch-process product images into standardized square PNG assets.
---

# Product Cutout Normalize

Use this skill when product photos need the same deterministic finishing pipeline:

- Gemini cutout from the original photo
- border cleanup to transparent
- preserve the full subject
- rotate to horizontal when the subject is taller than it is wide
- center on a `1024x1024` transparent canvas
- normalize the visible subject width to `820px`

## Quick Start

Run the bundled script:

```powershell
& ".\.venv\Scripts\python.exe" ".codex\skills\product-cutout-normalize\scripts\run_pipeline.py" "input_dir" "output_dir" --overwrite
```

Required environment:

- `GEMINI_API_KEY`
- `google-genai`
- `Pillow`

## Workflow

1. Confirm the request matches this standard pipeline. If the user asks for a different canvas size, subject width, or layout rule, pass explicit flags instead of changing the script.
2. Run the bundled script on the input directory.
3. If a result looks misaligned, inspect the alpha bounding box and small detached artifacts first; this pipeline already removes tiny alpha components by default.
4. Report the exact input and output directories used, plus any non-default flags.

## Script

Primary entry point:

- `scripts/run_pipeline.py`

Key flags:

- `--model`: Gemini image model, default `gemini-2.5-flash-image`
- `--canvas-size`: output square size, default `1024`
- `--target-width`: visible subject width after normalization, default `820`
- `--min-component-pixels`: remove detached alpha specks smaller than this, default `500`
- `--overwrite`: replace existing outputs in the destination directory

## Repo Integration

If the current project already has [`scripts/nano_banana_cutout.py`](/c:/Work/my_shop/scripts/nano_banana_cutout.py), prefer that repo script when the user wants the same pipeline inside this repository. Use the bundled skill script when the task is cross-project reuse or when you want the workflow to stay self-contained inside the skill.

scripts/run_pipeline.py source

The full scripts/run_pipeline.py source is preserved below without modification:

from __future__ import annotations

import argparse
import os
from collections import deque
from pathlib import Path

from PIL import Image

try:
    from google import genai
except ImportError as exc:  # pragma: no cover
    raise SystemExit(
        "Missing dependency: google-genai. Install it with "
        r"'.\.venv\Scripts\python.exe -m pip install google-genai'."
    ) from exc


PROMPT = (
    "Remove the entire background from this product photo and return only the product "
    "on a fully transparent background as a PNG. Keep the full product intact, preserve "
    "thin cable details, clean the inner loops and holes, and do not add any new objects "
    "or shadows."
)
DEFAULT_CANVAS_SIZE = 1024
DEFAULT_TARGET_WIDTH = 820
DEFAULT_MIN_COMPONENT_PIXELS = 500
SUPPORTED_EXTENSIONS = {".jpg", ".jpeg", ".png", ".webp"}


def is_light_background_pixel(r: int, g: int, b: int) -> bool:
    brightness = (r + g + b) / 3
    spread = max(r, g, b) - min(r, g, b)
    return brightness >= 170 and spread <= 35


def to_pil_image(image_obj) -> Image.Image:
    if isinstance(image_obj, Image.Image):
        return image_obj
    pil_image = getattr(image_obj, "_pil_image", None)
    if isinstance(pil_image, Image.Image):
        return pil_image
    as_pil = getattr(image_obj, "pil_image", None)
    if isinstance(as_pil, Image.Image):
        return as_pil
    raise TypeError(f"Unsupported image object type: {type(image_obj)!r}")


def make_transparent_from_borders(image: Image.Image) -> Image.Image:
    rgba = image.convert("RGBA")
    width, height = rgba.size
    pixels = rgba.load()

    visited: set[tuple[int, int]] = set()
    queue: deque[tuple[int, int]] = deque()

    def push_if_bg(x: int, y: int) -> None:
        if (x, y) in visited:
            return
        r, g, b, _ = pixels[x, y]
        if is_light_background_pixel(r, g, b):
            visited.add((x, y))
            queue.append((x, y))

    for x in range(width):
        push_if_bg(x, 0)
        push_if_bg(x, height - 1)
    for y in range(height):
        push_if_bg(0, y)
        push_if_bg(width - 1, y)

    while queue:
        x, y = queue.popleft()
        for nx, ny in ((x - 1, y), (x + 1, y), (x, y - 1), (x, y + 1)):
            if 0 <= nx < width and 0 <= ny < height:
                push_if_bg(nx, ny)

    for x, y in visited:
        pixels[x, y] = (0, 0, 0, 0)

    return rgba


def remove_small_components(image: Image.Image, min_component_pixels: int) -> Image.Image:
    if min_component_pixels <= 0:
        return image

    rgba = image.convert("RGBA")
    alpha = rgba.getchannel("A")
    width, height = rgba.size
    alpha_pixels = alpha.load()
    rgba_pixels = rgba.load()
    visited: set[tuple[int, int]] = set()

    for y in range(height):
        for x in range(width):
            if alpha_pixels[x, y] == 0 or (x, y) in visited:
                continue

            queue: deque[tuple[int, int]] = deque([(x, y)])
            visited.add((x, y))
            component: list[tuple[int, int]] = []

            while queue:
                cx, cy = queue.popleft()
                component.append((cx, cy))
                for nx, ny in ((cx - 1, cy), (cx + 1, cy), (cx, cy - 1), (cx, cy + 1)):
                    if 0 <= nx < width and 0 <= ny < height:
                        if alpha_pixels[nx, ny] == 0 or (nx, ny) in visited:
                            continue
                        visited.add((nx, ny))
                        queue.append((nx, ny))

            if len(component) < min_component_pixels:
                for px, py in component:
                    r, g, b, _ = rgba_pixels[px, py]
                    rgba_pixels[px, py] = (r, g, b, 0)

    return rgba


def normalize_product_image(
    image: Image.Image,
    canvas_size: int,
    target_width: int,
) -> Image.Image:
    rgba = image.convert("RGBA")
    bbox = rgba.getchannel("A").getbbox()
    if bbox is None:
        return Image.new("RGBA", (canvas_size, canvas_size), (0, 0, 0, 0))

    subject = rgba.crop(bbox)
    if subject.height > subject.width:
        subject = subject.rotate(-90, expand=True, resample=Image.Resampling.BICUBIC)
        rotated_bbox = subject.getchannel("A").getbbox()
        if rotated_bbox is not None:
            subject = subject.crop(rotated_bbox)

    scale = target_width / subject.width
    subject = subject.resize(
        (target_width, max(1, int(round(subject.height * scale)))),
        Image.Resampling.LANCZOS,
    )

    canvas = Image.new("RGBA", (canvas_size, canvas_size), (0, 0, 0, 0))
    offset_x = (canvas_size - subject.width) // 2
    offset_y = (canvas_size - subject.height) // 2
    canvas.alpha_composite(subject, (offset_x, offset_y))
    return canvas


def finalize_product_image(
    image: Image.Image,
    canvas_size: int,
    target_width: int,
    min_component_pixels: int,
) -> Image.Image:
    transparent = make_transparent_from_borders(image)
    cleaned = remove_small_components(transparent, min_component_pixels)
    return normalize_product_image(cleaned, canvas_size=canvas_size, target_width=target_width)


def save_first_image_part(
    response,
    dst: Path,
    canvas_size: int,
    target_width: int,
    min_component_pixels: int,
) -> None:
    parts = getattr(response, "parts", None)
    if parts is None and getattr(response, "candidates", None):
        parts = response.candidates[0].content.parts

    if not parts:
        raise RuntimeError("Model returned no content parts.")

    for part in parts:
        inline_data = getattr(part, "inline_data", None)
        if inline_data is None and isinstance(part, dict):
            inline_data = part.get("inline_data")

        if inline_data is None:
            continue

        if hasattr(part, "as_image"):
            image = to_pil_image(part.as_image())
            dst.parent.mkdir(parents=True, exist_ok=True)
            finalize_product_image(
                image,
                canvas_size=canvas_size,
                target_width=target_width,
                min_component_pixels=min_component_pixels,
            ).save(dst)
            return

        data = getattr(inline_data, "data", None)
        if data:
            dst.parent.mkdir(parents=True, exist_ok=True)
            with open(dst, "wb") as handle:
                handle.write(data)
            with Image.open(dst) as image:
                processed = finalize_product_image(
                    image,
                    canvas_size=canvas_size,
                    target_width=target_width,
                    min_component_pixels=min_component_pixels,
                )
                processed.save(dst.with_suffix(".png"))
            if dst.suffix.lower() != ".png":
                dst.unlink(missing_ok=True)
            return

    raise RuntimeError("Model returned text only and no edited image.")


def process_image(
    src: Path,
    dst: Path,
    client,
    model: str,
    canvas_size: int,
    target_width: int,
    min_component_pixels: int,
) -> None:
    with Image.open(src).convert("RGBA") as image:
        response = client.models.generate_content(
            model=model,
            contents=[PROMPT, image],
        )

    save_first_image_part(
        response,
        dst,
        canvas_size=canvas_size,
        target_width=target_width,
        min_component_pixels=min_component_pixels,
    )


def parse_args() -> argparse.Namespace:
    parser = argparse.ArgumentParser(
        description="Cut out product images with Gemini and normalize them to square transparent PNGs."
    )
    parser.add_argument("input_dir", type=Path)
    parser.add_argument("output_dir", type=Path)
    parser.add_argument("--model", default="gemini-2.5-flash-image")
    parser.add_argument("--canvas-size", type=int, default=DEFAULT_CANVAS_SIZE)
    parser.add_argument("--target-width", type=int, default=DEFAULT_TARGET_WIDTH)
    parser.add_argument("--min-component-pixels", type=int, default=DEFAULT_MIN_COMPONENT_PIXELS)
    parser.add_argument("--overwrite", action="store_true")
    return parser.parse_args()


def main() -> None:
    args = parse_args()
    api_key = os.environ.get("GEMINI_API_KEY")
    if not api_key:
        raise SystemExit("Missing GEMINI_API_KEY environment variable.")
    if not args.input_dir.is_dir():
        raise SystemExit(f"Input directory does not exist: {args.input_dir}")
    if args.canvas_size <= 0:
        raise SystemExit("--canvas-size must be positive.")
    if args.target_width <= 0 or args.target_width > args.canvas_size:
        raise SystemExit("--target-width must be positive and no larger than --canvas-size.")
    if args.min_component_pixels < 0:
        raise SystemExit("--min-component-pixels must be >= 0.")

    args.output_dir.mkdir(parents=True, exist_ok=True)
    client = genai.Client(api_key=api_key)

    for src in sorted(args.input_dir.iterdir()):
        if not src.is_file() or src.suffix.lower() not in SUPPORTED_EXTENSIONS:
            continue
        dst = args.output_dir / f"{src.stem}.png"
        if dst.exists() and not args.overwrite:
            print(f"skip {dst}")
            continue
        process_image(
            src,
            dst,
            client,
            args.model,
            canvas_size=args.canvas_size,
            target_width=args.target_width,
            min_component_pixels=args.min_component_pixels,
        )
        print(dst)


if __name__ == "__main__":
    main()

Download attachment: product-cutout-normalize.7z

How to Use Google Nano Banana for Image Cutouts

Thu, 09 Apr 2026 20:10:48 +0800

This article uses a practical Python script to show how to call Google’s Nano Banana image editing capability for product-image cutouts.

The goal of this implementation is very clear:

Read product images from a directory
Call a Google image model to remove the background
Apply one more round of local transparent-background cleanup to the returned image
Export the final result as a transparent PNG

If you already have a batch of white-background product photos, headset images, or cable images and want to quickly generate transparent-background assets for e-commerce use, this approach is very direct.

What this code does

This script is mainly divided into 4 parts:

Define a prompt so the model understands it should remove the background, keep the subject intact, and avoid adding shadows
Call the google-genai image generation interface
Extract the image result from the model response
Use local logic to turn light-colored edge background areas transparent and reduce leftover halos

In other words, it does not simply send the image to the model and stop there. It combines model editing with local post-processing.

Before you run it

Install the dependencies first:

`1`	`.\.venv\Scripts\python.exe -m pip install google-genai pillow`

How to get GEMINI_API_KEY

GEMINI_API_KEY is the key used when calling the Gemini API. According to Google’s official quickstart, if you do not already have one, you can create it directly in Google AI Studio.

The process is straightforward:

Open Google AI Studio.
Sign in with your Google account.
Find the Get API key or API keys page.
Create a new API key.
Copy the generated key.
Configure it as a local environment variable for the script to read.

If there is no available project on the page yet, you typically need to finish project initialization first and then return to the API key page to create the key.

After you have the key, configure the environment variable:

`1`	`$env:GEMINI_API_KEY="your_api_key"`

If you are using cmd, you can write:

`1`	`set GEMINI_API_KEY=your_api_key`

If both GEMINI_API_KEY and GOOGLE_API_KEY are set, the runtime will usually prefer GOOGLE_API_KEY, so it is better to keep only one of them to avoid confusion.

Example directory structure

The script accepts two arguments:

input_dir: input image directory
output_dir: output image directory

For example:

images/
  product1.jpg
  product2.png

output/

How to run it

Assuming the script file is named cutout.py, run it like this:

`1`	`.\.venv\Scripts\python.exe .\cutout.py .\images .\output`

If you want to switch models, you can also pass it explicitly:

`1`	`.\.venv\Scripts\python.exe .\cutout.py .\images .\output --model gemini-2.5-flash-image`

The script will iterate over these file types in the input directory:

.jpg
.jpeg
.png
.webp

After processing, it will generate transparent-background PNG files with matching names in the output directory.

Core API call flow

The key code that actually calls Google Nano Banana is here:

response = client.models.generate_content(
    model=model,
    contents=[PROMPT, image],
)

Two pieces of content are passed in here:

A text prompt, PROMPT
A PIL.Image

The prompt asks the model to remove the full background from the product image, keep only the subject, and pay attention to a few important requirements:

Keep the full product intact
Preserve thin lines and cable details
Clean up inner holes and loop areas
Do not add new objects
Do not add shadows

Prompts like this have a big effect on cutout quality, especially for details such as earphone wires, transparent edges, and hollow regions.

Why local post-processing is still needed

After the model returns the result, the script does not save it directly. It also runs make_transparent_from_borders(image).

The idea behind this step is:

Start from the outer border of the image and find light-colored background pixels
Use breadth-first search to mark all connected light-colored regions
Convert those regions to transparent in one pass

The benefit is that it can further clean up leftover white edges, light gray backgrounds, and edge areas that are not clean enough.

The condition used to decide whether a pixel is background is here:

def is_light_background_pixel(r: int, g: int, b: int) -> bool:
    brightness = (r + g + b) / 3
    spread = max(r, g, b) - min(r, g, b)
    return brightness >= 170 and spread <= 35

In simple terms, this means:

The overall color must be bright enough
The RGB channel difference cannot be too large

This is especially suitable for product images with white, light gray, or near-solid-color backgrounds.

Full source code

The complete source code is preserved below so you can reuse or modify it directly:

from __future__ import annotations

import argparse
import os
from pathlib import Path
from collections import deque

from PIL import Image

try:
    from google import genai
except ImportError as exc:  # pragma: no cover
    raise SystemExit(
        "Missing dependency: google-genai. Install it with "
        r"'.\.venv\Scripts\python.exe -m pip install google-genai'."
    ) from exc


PROMPT = (
    "Remove the entire background from this product photo and return only the product "
    "on a fully transparent background as a PNG. Keep the full product intact, preserve "
    "thin cable details, clean the inner loops and holes, and do not add any new objects "
    "or shadows."
)


def is_light_background_pixel(r: int, g: int, b: int) -> bool:
    brightness = (r + g + b) / 3
    spread = max(r, g, b) - min(r, g, b)
    return brightness >= 170 and spread <= 35


def to_pil_image(image_obj) -> Image.Image:
    if isinstance(image_obj, Image.Image):
        return image_obj
    pil_image = getattr(image_obj, "_pil_image", None)
    if isinstance(pil_image, Image.Image):
        return pil_image
    as_pil = getattr(image_obj, "pil_image", None)
    if isinstance(as_pil, Image.Image):
        return as_pil
    raise TypeError(f"Unsupported image object type: {type(image_obj)!r}")


def make_transparent_from_borders(image: Image.Image) -> Image.Image:
    rgba = image.convert("RGBA")
    width, height = rgba.size
    pixels = rgba.load()

    visited: set[tuple[int, int]] = set()
    queue: deque[tuple[int, int]] = deque()

    def push_if_bg(x: int, y: int) -> None:
        if (x, y) in visited:
            return
        r, g, b, _ = pixels[x, y]
        if is_light_background_pixel(r, g, b):
            visited.add((x, y))
            queue.append((x, y))

    for x in range(width):
        push_if_bg(x, 0)
        push_if_bg(x, height - 1)
    for y in range(height):
        push_if_bg(0, y)
        push_if_bg(width - 1, y)

    while queue:
        x, y = queue.popleft()
        for nx, ny in ((x - 1, y), (x + 1, y), (x, y - 1), (x, y + 1)):
            if 0 <= nx < width and 0 <= ny < height:
                push_if_bg(nx, ny)

    for x, y in visited:
        pixels[x, y] = (0, 0, 0, 0)

    return rgba


def save_first_image_part(response, dst: Path) -> None:
    parts = getattr(response, "parts", None)
    if parts is None and getattr(response, "candidates", None):
        parts = response.candidates[0].content.parts

    if not parts:
        raise RuntimeError("Model returned no content parts.")

    for part in parts:
        inline_data = getattr(part, "inline_data", None)
        if inline_data is None and isinstance(part, dict):
            inline_data = part.get("inline_data")

        if inline_data is None:
            continue

        if hasattr(part, "as_image"):
            image = to_pil_image(part.as_image())
            dst.parent.mkdir(parents=True, exist_ok=True)
            make_transparent_from_borders(image).save(dst)
            return

        data = getattr(inline_data, "data", None)
        mime_type = getattr(inline_data, "mime_type", "")
        if data:
            dst.parent.mkdir(parents=True, exist_ok=True)
            with open(dst, "wb") as handle:
                handle.write(data)
            with Image.open(dst) as img:
                processed = make_transparent_from_borders(img)
                processed.save(dst.with_suffix(".png"))
            if dst.suffix.lower() != ".png":
                dst.unlink(missing_ok=True)
            return

    raise RuntimeError("Model returned text only and no edited image.")


def process_image(src: Path, dst: Path, client, model: str) -> None:
    with Image.open(src).convert("RGBA") as image:
        response = client.models.generate_content(
            model=model,
            contents=[PROMPT, image],
        )
    save_first_image_part(response, dst)


def main() -> None:
    parser = argparse.ArgumentParser(description="Use Nano Banana / Gemini image editing to cut out product images.")
    parser.add_argument("input_dir", type=Path)
    parser.add_argument("output_dir", type=Path)
    parser.add_argument("--model", default="gemini-2.5-flash-image")
    args = parser.parse_args()

    api_key = os.environ.get("GEMINI_API_KEY")
    if not api_key:
        raise SystemExit("Missing GEMINI_API_KEY environment variable.")

    client = genai.Client(api_key=api_key)
    exts = {".jpg", ".jpeg", ".png", ".webp"}

    for src in sorted(args.input_dir.iterdir()):
        if not src.is_file() or src.suffix.lower() not in exts:
            continue
        dst = args.output_dir / f"{src.stem}.png"
        process_image(src, dst, client, args.model)
        print(dst)


if __name__ == "__main__":
    main()

Good places to improve it further

If you plan to use this script for batch production, you can continue improving it in these directions:

Add retry logic so one failed image does not stop the whole batch
Add logs to make it easier to identify which image failed
Make background thresholds configurable
Support recursive scanning of subdirectories
Add a side-by-side preview of the original and processed result

Summary

If you only want the shortest explanation of how to use Google Nano Banana for cutouts, the core process is just three steps:

Install google-genai and Pillow
Set GEMINI_API_KEY
Pass the prompt and image to client.models.generate_content()

The value of this code is that it does more than just call the model. It also adds transparent-background post-processing, which makes it more suitable for direct product-image cutout work.

What are Ollama cloud models and how do you use them

Thu, 09 Apr 2026 18:42:32 +0800

If you already use Ollama to run local models, cloud models are easy to understand.

There is only one core difference:
local models run on your own machine, while cloud models run on Ollama’s cloud infrastructure and return the result to you.

What are Ollama cloud models

Ollama cloud models keep the Ollama workflow, but move the actual computation from your local machine to the cloud.

The main benefits are:

Less pressure on local hardware
Easier access to larger models that your machine cannot run well
You can keep using the familiar Ollama workflow

How they differ from local models

Item	Local models	Cloud models
Runtime location	Your machine	Cloud
Hardware requirements	High	Low
Latency	Usually lower	Affected by network
Privacy	Stronger	Requests are sent to the cloud

If you care more about privacy, low latency, and offline use, local models are a better fit.
If your hardware is limited but you still want to use larger models, cloud models are more convenient.

How to identify a cloud model

At the moment, Ollama cloud models are typically labeled with a -cloud suffix, for example:

`1`	`gpt-oss:120b-cloud`

The available model list may change over time, so the official Ollama pages should be treated as the source of truth.

How to use them

First, sign in:

`1`	`ollama signin`

After that, run a cloud model directly:

`1`	`ollama run gpt-oss:120b-cloud`

If you are calling it from code, you can also configure an API key:

`1`	`export OLLAMA_API_KEY=your_api_key`

Python example:

import os
from ollama import Client

client = Client(
    host="https://ollama.com",
    headers={"Authorization": "Bearer " + os.environ["OLLAMA_API_KEY"]},
)

messages = [
    {"role": "user", "content": "Why is the sky blue?"}
]

for part in client.chat("gpt-oss:120b-cloud", messages=messages, stream=True):
    print(part["message"]["content"], end="", flush=True)

Summary

Ollama cloud models can be summarized in one sentence:

the commands are almost the same, but the model is no longer running on your local machine.

If your computer cannot handle large models well, but you still want to keep the Ollama workflow, cloud models are a very direct option.

Windows Task Manager data stops updating: the refresh speed is usually set to Paused

Thu, 09 Apr 2026 18:15:53 +0800

Sometimes when you open Windows Task Manager, the data on the Processes or Performance tab appears frozen. CPU, memory, disk, or network values may stay unchanged for a long time. At first glance this can look like a system problem, but in reality running programs, network traffic, and resource usage are still changing normally.

In most cases, the system is not actually stuck. The more likely reason is that Task Manager’s refresh speed has been changed to Paused.

Symptoms

Common signs include:

CPU, memory, and other values on the Processes tab stop changing
Graphs on the Performance tab no longer update
Programs are clearly still running, but Task Manager looks frozen

Here is an example of what the issue looks like:

Cause

Task Manager lets you adjust the Update speed, with options such as High, Normal, Low, or Paused.

If this setting is changed to Paused, the statistics shown in the interface stop refreshing. That is why CPU, memory, or network information can appear to be completely frozen.

As shown below, this option is usually available from the View menu in Task Manager:

Fix

Check the following:

Open Task Manager
Click the View menu
Find Update speed
Check whether it is currently set to Paused
Change it back to Normal or High

After that, watch the Processes or Performance tab again. In most cases, the data will start updating normally right away.

Additional notes

If the data still does not refresh after switching back to Normal, check a few other possibilities:

Whether you are using system-tuning tools or third-party performance monitoring software
Whether you are connected through a remote session and the interface is not refreshing correctly
Whether Task Manager itself is stuck, in which case you can close it and open it again

That said, in most cases this issue is simply caused by Update speed being accidentally set to Paused, so checking that first is usually the fastest fix.

How to Download a GGUF Model from Hugging Face and Import It into Ollama

Thu, 09 Apr 2026 11:00:07 +0800

If a model is not available in the official Ollama library, or if you want to use a specific GGUF file from Hugging Face, you can download it manually and then import it into Ollama.

Step 1: Download the GGUF file from Hugging Face

First, find the target model’s GGUF file on Hugging Face. You will usually see multiple quantized versions, such as:

Q4_K_M
Q5_K_M
Q8_0

Which version you choose depends on your VRAM, RAM, and your tradeoff between speed and quality. After downloading, place the .gguf file in a fixed directory so you can reference it from the Modelfile.

Step 2: Write the Modelfile

Create a Modelfile in the same directory as the model file. The most basic version looks like this:

`1`	`FROM ./model.gguf`

If the filename is different, replace it with the actual filename, for example:

`1`	`FROM ./gemma-3-12b-it-q4_k_m.gguf`

If your goal is just to get it running, this single FROM line is usually enough.

Step 3: Import it into Ollama

Then run:

`1`	`ollama create myModelName -f Modelfile`

myModelName is the local model name you want to use inside Ollama
-f Modelfile tells Ollama to create the model from that file

Once the creation succeeds, the GGUF file becomes a local model that you can call directly.

Step 4: Run the model

After creation, run:

`1`	`ollama run myModelName`

From that point on, it works much like a model pulled with ollama pull.

How to inspect an existing model’s Modelfile

If you are not sure how to write a Modelfile, you can inspect the configuration of an existing model directly:

`1`	`ollama show --modelfile llama3.2`

This command prints the Modelfile for llama3.2, which is useful as a reference for:

How FROM should be written
How the template and system prompt are structured
How parameters are declared

When this approach makes sense

This manual Hugging Face import flow is useful when:

The model you want is not available in Ollama’s official library
You want a specific quantized variant
You have already downloaded the GGUF file manually
You want finer control over how the model is packaged

If Ollama already provides an official version, using pull is usually simpler. But when you need a specific quantization or a custom wrapper, GGUF + Modelfile gives you more flexibility.

Common notes

The path after FROM must match the actual location of the .gguf file.
If the filename contains spaces or special characters, it is better to rename it first.
Different GGUF quantization levels can greatly affect memory use and speed, so successful import does not guarantee smooth runtime performance.
If the model is a chat model, you may still need to adjust the prompt template later for better results.

Conclusion

Downloading a GGUF file from Hugging Face and importing it into Ollama is not complicated. Prepare the model file, write a minimal Modelfile, then run ollama create, and you can bring a third-party GGUF model into your Ollama workflow.

How to Troubleshoot Slow `ollama pull` Model Downloads

Thu, 09 Apr 2026 10:42:39 +0800

ollama pull model_name:tag can be very slow in some regions, and the download process is not always stable.

If your issue looks like repeated interruptions halfway through a large model download, with errors such as TLS handshake timeout or unexpected EOF, the bottleneck may not be registry.ollama.ai itself, but the actual download path after the redirect.

This article walks through a simple troubleshooting approach: first get the real model file URLs, then confirm where the traffic actually ends up, and finally optimize only the domains that matter.

Get the model file download URLs

You can use the following project to extract the manifest and blob download URLs for an Ollama model directly:

https://github.com/Gholamrezadar/ollama-direct-downloader

Using gemma4:latest as an example, you can extract links like the following.

Manifest URL

`1`	`https://registry.ollama.ai/v2/library/gemma4/manifests/latest`

Blob URLs

https://registry.ollama.ai/v2/library/gemma4/blobs/sha256:f0988ff50a2458c598ff6b1b87b94d0f5c44d73061c2795391878b00b2285e11
https://registry.ollama.ai/v2/library/gemma4/blobs/sha256:4c27e0f5b5adf02ac956c7322bd2ee7636fe3f45a8512c9aba5385242cb6e09a
https://registry.ollama.ai/v2/library/gemma4/blobs/sha256:7339fa418c9ad3e8e12e74ad0fd26a9cc4be8703f9c110728a992b193be85cb2
https://registry.ollama.ai/v2/library/gemma4/blobs/sha256:56380ca2ab89f1f68c283f4d50863c0bcab52ae3f1b9a88e4ab5617b176f71a3

If you only want a quick verification, you can also download the manifest and blobs directly with curl:

curl -L "https://registry.ollama.ai/v2/library/gemma4/manifests/latest" -o "latest"
curl -L "https://registry.ollama.ai/v2/library/gemma4/blobs/sha256:f0988ff50a2458c598ff6b1b87b94d0f5c44d73061c2795391878b00b2285e11" -o "sha256-f0988ff50a2458c598ff6b1b87b94d0f5c44d73061c2795391878b00b2285e11"
curl -L "https://registry.ollama.ai/v2/library/gemma4/blobs/sha256:4c27e0f5b5adf02ac956c7322bd2ee7636fe3f45a8512c9aba5385242cb6e09a" -o "sha256-4c27e0f5b5adf02ac956c7322bd2ee7636fe3f45a8512c9aba5385242cb6e09a"
curl -L "https://registry.ollama.ai/v2/library/gemma4/blobs/sha256:7339fa418c9ad3e8e12e74ad0fd26a9cc4be8703f9c110728a992b193be85cb2" -o "sha256-7339fa418c9ad3e8e12e74ad0fd26a9cc4be8703f9c110728a992b193be85cb2"

The real download URL after the redirect

If you try downloading one of the blobs with wget, you will notice that the request does not stay on registry.ollama.ai. It gets redirected to a Cloudflare R2 object storage URL:

`1`	`wget https://registry.ollama.ai/v2/library/gemma4/blobs/sha256:4c27e0f5b5adf02ac956c7322bd2ee7636fe3f45a8512c9aba5385242cb6e09a`

There are a few key details in the log:

registry.ollama.ai returns 307 Temporary Redirect
The final download URL lands on *.r2.cloudflarestorage.com
The large file transfer is actually being served by the object storage domain behind the redirect

This matters because if your proxy or routing rules only cover registry.ollama.ai but not *.r2.cloudflarestorage.com, downloads can still be slow or repeatedly interrupted.

Here is one example of an actual redirect log:

wget https://registry.ollama.ai/v2/library/gemma4/blobs/sha256:4c27e0f5b5adf02ac956c7322bd2ee7636fe3f45a8512c9aba5385242cb6e09a
--2026-04-09 09:22:04--  https://registry.ollama.ai/v2/library/gemma4/blobs/sha256:4c27e0f5b5adf02ac956c7322bd2ee7636fe3f45a8512c9aba5385242cb6e09a
Resolving registry.ollama.ai (registry.ollama.ai)... 104.21.75.227, 172.67.182.229, 2606:4700:3034::ac43:b6e5, ...
Connecting to registry.ollama.ai (registry.ollama.ai)|104.21.75.227|:443... connected.
HTTP request sent, awaiting response... 307 Temporary Redirect
Location: https://dd20bb891979d25aebc8bec07b2b3bbc.r2.cloudflarestorage.com/ollama/docker/registry/v2/blobs/sha256/4c/4c27e0f5b5adf02ac956c7322bd2ee7636fe3f45a8512c9aba5385242cb6e09a/data?... [following]
--2026-04-09 09:22:05--  https://dd20bb891979d25aebc8bec07b2b3bbc.r2.cloudflarestorage.com/ollama/docker/registry/v2/blobs/sha256/4c/4c27e0f5b5adf02ac956c7322bd2ee7636fe3f45a8512c9aba5385242cb6e09a/data?...
Resolving dd20bb891979d25aebc8bec07b2b3bbc.r2.cloudflarestorage.com (dd20bb891979d25aebc8bec07b2b3bbc.r2.cloudflarestorage.com)... 172.64.66.1, 2606:4700:2ff9::1
Connecting to dd20bb891979d25aebc8bec07b2b3bbc.r2.cloudflarestorage.com|172.64.66.1|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 9608338848 (8.9G) [application/octet-stream]

Adjust your network settings

Once you confirm the real download path, the troubleshooting direction becomes much clearer.

If you are using a proxy, split routing, or custom DNS, check these first:

Whether registry.ollama.ai and *.r2.cloudflarestorage.com are using the same stable route
Whether your proxy rules cover only the former but miss the latter
Whether your current outbound path is suitable for sustained multi-GB downloads

The key issue here is not simply whether the official site opens, but whether the redirected object storage path is stable enough for long-running large-file transfers. In many cases, the real bottleneck is the Cloudflare R2 layer rather than the registry domain in front of it.

Before-and-after comparison

Here is one real-world example while downloading gemma4:31b-it-q8_0.

Before adjusting the network path, the download was slow and failed midway:

PS C:\Users\knightli> ollama run gemma4:31b-it-q8_0
pulling manifest
pulling a0feadb736f5:  38% ▕██████████████████████                                    ▏  12 GB/ 33 GB  1.2 MB/s   4h40m
Error: max retries exceeded: unexpected EOF

After the adjustment, the same model download became noticeably faster and more stable:

1
2
3

PS C:\Users\knightli> ollama run gemma4:31b-it-q8_0
pulling manifest
pulling a0feadb736f5:  46% ▕████████████████████████████████████████████████████████████████▏ 15 GB/ 33 GB  8.5 MB/s  35m23s

This does not mean every network environment will see the same improvement, but it does support one useful conclusion: the bottleneck may be the actual large-file download path rather than the Ollama client itself.

A more practical troubleshooting order

If you run into the same issue, this order usually works well:

Run ollama pull or ollama run once and confirm the issue is reproducible.
Test a blob URL with wget or curl -L and confirm whether it redirects to *.r2.cloudflarestorage.com.
Adjust your proxy or routing only for the real download domain, then test speed and stability again.

The benefit of this order is that each step validates one clear hypothesis, so you do not have to troubleshoot blindly.

Conclusion

When ollama pull is slow, the problem is often not that registry.ollama.ai is unreachable, but that the Cloudflare R2 path actually serving the large files is unstable.

So instead of retrying over and over, a better approach is to identify the real download path first and optimize the network route where the traffic actually lands.

Anthropic and OpenClaw Timeline: The Full Sequence of Events

Wed, 08 Apr 2026 19:48:42 +0800

Background

On April 4, 2026, Anthropic announced that Claude subscriptions would no longer cover third-party tools such as OpenClaw.

The direct user-level impact was that third-party workflows previously relying on the subscription path for Claude access had to move to alternative access methods or switch to other models.

Timeline (January to April 2026)

January 2026

According to public reports, Anthropic asked the project formerly known as Clawdbot to change its name, citing pronunciation similarity to Claude.

During the same period, community feedback began to appear regarding restrictions on third-party access via subscription credentials.

February 2026

The relevant restrictions were written into the terms of service, further clarifying the boundary between subscriptions and third-party automated invocation.

In the same month, OpenClaw released v4.0 and refactored its underlying architecture into a pluggable model backend. In other words, the model was no longer a single hardcoded entry point and could be switched across multiple providers.

March 2026

Anthropic released Claude Dispatch and Computer Use, covering capabilities such as remote task execution and desktop operation.

In subsequent updates, OpenClaw continued building its compatibility layer, unifying differences across model providers in authentication, tool-call formats, and response schemas, thereby reducing migration costs when switching models.

Public reports also noted that OpenClaw and Anthropic communicated in late March, but the overall strategic direction remained unchanged.

April 4, 2026

Anthropic formally executed the subscription coverage cutoff for third-party tools.

This marked the execution phase of policy adjustments that had been underway for several months.

April 5, 2026

OpenClaw released v4.5 with several main actions:

Reprioritizing model entry points in the onboarding flow
Integrating alternative model paths such as GPT-5.4
Continuing adaptation work for task flow and interaction experience

Based on the release timing, OpenClaw’s switchover capability was not built entirely ad hoc, but rested on the multi-model architecture work launched since February.

Two Parallel Directions in the Process

Viewed along the timeline, both parties advanced different priorities during the same period:

Anthropic: tightening subscription boundaries and integrating official product capabilities
OpenClaw: strengthening model replaceability and cross-model compatibility

These two routes are not inherently contradictory, but they do create competition over entry-point ownership and where user workflows accumulate.

Current Status (as of April 2026)

Based on publicly available information, the following can be confirmed:

The subscription coverage cutoff has been executed
OpenClaw has completed its primary model-path transition and continues iterating
Whether users perceive major changes depends on how strongly their workflows rely on any single model

What to Watch Next

Going forward, the more meaningful signals are not from this single event itself, but from three areas:

Whether boundaries between subscription plans and API usage become more explicit
The long-term performance of multi-model agents in stability, cost, and user experience
Whether user workflows settle primarily at the model layer, tool layer, or a hybrid layer between the two

Gemma 4 on Raspberry Pi 5: It Works, But Responses Are Slow

Wed, 08 Apr 2026 18:42:00 +0800

I ran a near-limit experiment: running Gemma 4 on a Raspberry Pi 5 (8GB RAM). I was not targeting larger variants, only the smallest E2B model.

Conclusion first: it runs and it is usable, but it fits low-interaction workflows better than real-time chat.

Test Environment

Device: Raspberry Pi 5 (4-core CPU, 8GB RAM)
OS: Ubuntu Server (no GUI)
Access method: SSH
Runtime: LM Studio CLI (command-line-only mode)
Model: Gemma 4 E2B (about 4.5GB)

Step 1: Install and Start LM Studio CLI

I installed the LM Studio CLI build on the Pi, then started the service and checked available commands.

For a terminal-only setup, this deployment mode is a good fit for Raspberry Pi.

Step 2: Move Model Storage to SSD

To avoid heavy SD card writes, I switched model download storage to an external SSD.

On Raspberry Pi 5, SSD usage is much more practical than on older models. For long-term local model runs, SSD is strongly recommended.

Step 3: Download and Load Gemma 4 E2B

After download, the model loaded into memory successfully.

According to official information, Gemma 4 includes:

Tool-calling support for agent-style workflows (function calling)
Multimodal capabilities (image/video; smaller models also include audio-related capability)
128K context window
Apache 2.0 license (commercial use allowed)

Given Raspberry Pi hardware limits, E2B is the most practical tier to start with.

Step 4: Start API and Enable LAN Access

After loading, I started the API on local port 4000 and confirmed model listing works via HTTP.

The issue: by default, it only listens on localhost, so other LAN devices cannot access it directly.

Since host binding was not exposed by the startup options, I used socat for port forwarding, bridging an external Pi port to LM Studio’s internal port.

Result: successful. I could query the model list from a MacBook on the same LAN.

Step 5: Connect to Editor (Zed)

LM Studio’s local server is OpenAI-API-compatible, so most tools that support custom base_url can connect.

I added a new LLM provider in Zed pointing to the Pi-hosted Gemma 4 instance, and in-editor chat worked.

Practical Usability

This setup is suitable for:

Local automation scripts
Low-concurrency, low-real-time assistant tasks
Personal learning and edge-device experimentation

Less suitable for:

High-frequency interactive chat
Development collaboration scenarios sensitive to response latency

Conclusion

Running Gemma 4 (E2B) on Raspberry Pi 5 is feasible, and the practical output quality is better than expected.

If your goal is offline operation, tool integration, and lightweight-to-mid tasks, this setup is worth trying. If your goal is smooth real-time interaction, stronger hardware is still the better choice.

Connect OpenClaw to Local Gemma 4: Complete Setup Guide

Wed, 08 Apr 2026 18:18:00 +0800

This guide shows how to connect OpenClaw to a local Gemma 4 model through Ollama.

If you have not deployed Gemma 4 locally yet, start here:

How to Run Gemma 4 on a Laptop: 5-Minute Local Setup Guide

Step 1: Start the Ollama API Service

Start Ollama first:

`1`	`ollama serve`

Then verify the API quickly with:

curl http://localhost:11434/api/generate -d '{
  "model": "gemma4:12b",
  "prompt": "Hello"
}'

If you get a model response, your local API is ready.

Step 2: Configure OpenClaw to Use Ollama

The OpenClaw config file is usually located at:

`1`	`~/.openclaw/config.yaml`

Edit config.yaml and add a local model entry under models:

models:
  # Your existing model config...

  gemma4-local:
    provider: ollama
    base_url: http://localhost:11434
    model: gemma4:12b
    timeout: 120s

Step 3: Set Default Model (Optional)

If you want Gemma 4 as the default model:

`1`	`default_model: gemma4-local`

Step 4: Restart and Verify OpenClaw

Restart OpenClaw:

`1`	`openclaw restart`

List available models:

`1`	`openclaw models list`

Run a quick chat test:

`1`	`openclaw chat --model gemma4-local "Hello"`

If the chat returns normally, OpenClaw is successfully connected to local Gemma 4.

Common Troubleshooting

connection refused: make sure ollama serve is running.
Model not found: check model name with ollama list (for example gemma4:12b).
Timeout: increase timeout and test a smaller model first.

How to Run Gemma 4 on a Laptop: 5-Minute Local Setup Guide

Wed, 08 Apr 2026 18:06:00 +0800

If you want to run Gemma 4 locally on a laptop, Ollama is one of the fastest and simplest options. Even without complex setup, you can usually get it running in about five minutes.

Step 1: Install Ollama

Open https://ollama.com and download the installer for your OS.
Complete installation based on your system:

macOS: drag it to Applications.
Windows: run the .exe installer.
Linux: use the install script from the official site.

After installation, Ollama runs as a background service. Beyond initial setup, daily usage is mostly simple commands.

Step 2: Download a Gemma 4 Model

Open a terminal and run:

`1`	`ollama pull gemma4:4b`

If your machine is stronger, you can switch to 12b or 27b. Once downloaded, the model is stored locally.

Check downloaded models with:

`1`	`ollama list`

Step 3: Run the Model

`1`	`ollama run gemma4:4b`

This opens an interactive chat session in your terminal. Type your prompt and press Enter. To exit, type:

/bye

If you prefer a browser chat UI, you can pair it with Open WebUI. It wraps Ollama with a local web interface and is usually quick to set up with Docker.

Laptop Performance Tips

Apple Silicon (M2/M3/M4): Metal acceleration is enabled by default, and 12B can run well.
NVIDIA GPU: CUDA is used automatically when a compatible GPU is detected. Keep drivers updated.
CPU-only inference: works, but larger models will be slower. For most CPU-only setups, 4B is the practical default.
Free memory before loading large models: as a rough rule, each billion parameters needs about 0.5GB to 1GB RAM.

How to Choose a Model

Gemma 4 1B: good for lightweight Q&A, simple summarization, and quick lookups; limited on complex reasoning.
Gemma 4 4B: best for most daily tasks (writing help, coding help, document summarization) with strong speed/quality balance.
Gemma 4 12B: better for longer context and more complex tasks, especially coding and reasoning.
Gemma 4 27B: better for high-demand workloads and closer to frontier-cloud quality, but needs significantly stronger hardware.

How to Install and Run Gemma 4 on Android: Complete Getting-Started Guide

Wed, 08 Apr 2026 17:55:53 +0800

If you want to run Gemma 4 offline on your phone, this guide walks you through the full process from setup to practical usage.

Step 1: Get the App

Google AI Edge Gallery is currently not available on Google Play, so you need to install it via APK sideloading.

On your Android device, go to:

Settings -> Apps -> Special app access -> Install unknown apps

Then:

Find your browser (for example, Chrome or Firefox) and enable “Allow from this source.”
Open the Google AI Edge Gallery GitHub Releases page in your mobile browser.

URL: https://github.com/google-ai-edge/gallery/releases

Download the latest .apk package.
After the download completes, open the file from notifications or your file manager and follow the prompts.

With a stable connection, this step usually takes around 2 minutes.

Step 2: Open the App and Grant Permissions

When you first open AI Edge Gallery, it will request storage permission to save model files. It’s best to allow this; otherwise, the app cannot download or load models.

You will typically see these sections on the home screen:

Ask Image: Vision tasks (describe images, answer questions about photos)
AI Chat: Standard text chat
Summarize: Paste text and generate summaries
Smart Reply: Generate reply suggestions

For most users, AI Chat is the primary entry point.

Step 3: Download a Gemma 4 Model

Enter AI Chat.
Tap Get Models when prompted.
Choose a Gemma 4 model from the list (model size is shown).
Pick based on your device capability; if your phone has 8GB RAM, start with Gemma 4 4B.
Tap Download and let it run in the background.

Note: Larger models take longer to download. You can download multiple models and switch between them later. Downloaded models stay on your device, so you do not need to re-download them.

Step 4: Start Chatting

After the model download is finished:

Tap the model name to load it (the first load usually takes 10 to 30 seconds depending on model size and device performance).
Enter your prompt in the chat box and send it.
The model generates responses locally, and your data does not leave the phone.

The first reply is often slower due to model warm-up. Later messages in the same session are usually faster.

Step 5: Try Vision Features (Gemma 4 Multimodal)

If you downloaded a Gemma 4 multimodal variant:

Go back to the main menu and open Ask Image.
Select an image or take a photo.
Ask a question (for example, “What’s in this image?” or “Is there any text I should pay attention to?”).
Wait for the model to analyze the image locally and return a result.

This feature works offline, and your image is not sent to external servers.

Memory Die Identification Guide: How to Read Samsung, Micron, and SK hynix Codes

Mon, 06 Apr 2026 17:06:21 +0800

When buying memory, selecting dies, or tuning for overclocking, the most common question is: what die is actually used on this module?

This article organizes a reusable identification workflow around three common vendors: Samsung, Micron, and SK hynix. The examples here are mainly DDR4.

Start With the Method

Check the full on-chip marking and complete part code first.
Cross-check with official vendor lookup tools.
Use forum tables and community experience only as the final layer.

If you rely only on software detection, or only on one letter in the code, misidentification is very likely.

Samsung Dies

1) Naming Rule Diagrams

Common readable fields in Samsung DDR4 die codes:

Vendor prefix: K
DRAM class: 4
Generation: A = DDR4
Density: 4G/8G/AG/BG = 4/8/16/32Gb
I/O width: 04/08/16 = x4/x8/x16
Revision generation: M/A/B/C/D/E/F/G
Speed bins: commonly PB/RC/TD/...

2) Real Sample

Sample breakdown:

Line 1 SEC 843: commonly indicates production batch info.
Line 2 K4A4G08: 4G08 commonly maps to density/width.
Line 3 ...TD: TD commonly maps to DDR4-2666 CL19.
Line 4 corner mark: useful as reference, but should not be used as the only conclusion.

Micron Dies

1) Marking Layout and Sample

Using 7UE75 / D9VPP as an example:

7UE75 can indicate date batch, revision, and diffusion/assembly location info.
D9VPP is the FBGA code, and should be checked in the official tool next.

2) Official FBGA Lookup

Lookup URL:

https://www.micron.com/support/tools-and-utilities/fbga

3) Part Number Mapping

Sample: MT40A1G8SA-075:E

40: DDR4 family
1G8: 8Gb x8
512M16: 8Gb x16
075: commonly maps to DDR4-2666 CL19
083: commonly maps to DDR4-2400 CL17
093E: commonly maps to DDR4-2133 CL15
E: maps to E-die revision

Spectek (Large-S, Micron White-Chip Line)

Common format: PS029-093 TP

PS029: can be queried on the Spectek website.
093: commonly maps to a speed/timing bin.
TP: commonly used as a quality grade mark.

Lookup URL:

https://www.spectek.com/menus/mark_code.aspx

SK hynix Dies

1) Naming Rule Diagrams

Common readable fields in SK hynix DDR4 codes:

PRODUCT FAMILY: 5 = DRAM
PRODUCT MODE: A = DDR4 SDRAM
POWER SUPPLY: N = VDD/VDDQ 1.2V
DENSITY: 1G/2G/4G/8G/AG/BG
ORGANIZATION: 4/8/6 = x4/x8/x16
DIE TYPE: N = Non-TSV, T = TSV
DIE GENERATION: M/A/B/C/D/E/F/G
SPEED: TF/UH/UL/VK/VN/WM/XN
PACKAGE TYPE: F/J/M/P/2/4
Temperature/power flag: C, R

2) Real Sample

Sample H5AN8G8NCJR:

8G8: commonly means 8Gb x8.
C: commonly used for C-die generation identification.
VK (visible on the next line): commonly maps to DDR4-2666 19-19-19.
Tail batch code (for example 829A) can help estimate production timing.

Common Pitfalls

AFR/CJR/MFR are common community names, but not the full official definition.
The same memory model may change die source across production batches.
With white chips, relabeled chips, or mixed batches, software-only detection is error-prone.

References and Notes

This article is for hardware education and troubleshooting, not a purchase guarantee.
Final identification should be based on physical markings and official lookup results.
Reference (compiled): https://www.bilibili.com/read/cv2519652/?opus_fallback=1
Official tools (lookup/reference):
Micron FBGA: https://www.micron.com/support/tools-and-utilities/fbga
Spectek Mark Code: https://www.spectek.com/menus/mark_code.aspx
Spectek reference page: http://am.adianshi.com:6805/%E5%BC%80%E5%8D%A1%E8%BD%AF%E4%BB%B6/%E6%96%87%E6%A1%A3/spectek_flash.pdf

Using Agent Skills to Replace Copilot's 'Generate Commit Message' in VS Code

Mon, 06 Apr 2026 13:09:49 +0800

GitHub Copilot’s “Generate Commit Message” in VS Code is very useful. Once the quota is exhausted, the reset cycle can feel long. This post is a practical attempt to replace that feature with local Agent Skills.

Problem and Goal

The goal of this post is to provide a practical alternative: use git-commit-push-zh skill agents to complete standardized commits and pushes.

Alternative: `git-commit-push-zh`

This skill turns your current changes into a fixed workflow:

Check change status.
Confirm the current branch.
Stage changes.
Generate a Chinese commit message.
Run commit.
Push to the remote branch.

The corresponding commands are:

git status --short
git branch --show-current
git add -A
git commit -m "<中文提交信息>"
git push origin <当前分支>

Suggested Commit Message Convention

Use this format consistently:

`1`	`<类型>(<范围>): <中文摘要>`

Type examples:

feat: New feature
fix: Bug fix
docs: Documentation update
refactor: Refactoring
chore: Maintenance changes

Examples:

feat(site): 新增全站 head 广告脚本注入
fix(i18n): 修正 relref 相关文章链接路径
chore(content): 合并 AI 工作流分类到 AI工具

Common Failure Scenarios

nothing to commit: no new changes to commit; stop before pushing.
push failed: check permissions, remote branch state, and conflicts first.
SSH/permission issues: verify credentials and access, then retry.

Appendix: Original `SKILL.md`

The content below is the original git-commit-push-zh document, preserved as-is for reuse and maintenance.

---
name: git-commit-push-zh
description: 在当前 Git 仓库中将“当前更改”完成一次标准提交流程：检查状态、暂存变更、生成中文提交信息、执行 commit 并 push 到当前分支对应远端。用户提出“提交代码”“提交当前更改”“生成中文提交信息并推送”“git commit push 中文说明”等请求时使用。
---

# 中文提交并推送

使用此技能将当前仓库改动一次性提交并推送到远端。

## 工作流程

1. 查看变更状态：`git status --short`。
2. 确认当前分支：`git branch --show-current`。
3. 暂存当前变更：`git add -A`。
4. 生成中文提交信息（简洁、可检索）。
5. 执行提交：`git commit -m "<中文提交信息>"`。
6. 执行推送：`git push origin <当前分支>`。

## 提交信息规范（中文）

1. 建议格式：`<类型>(<范围>): <中文摘要>`。
2. 类型示例：`feat`、`fix`、`chore`、`docs`、`refactor`。
3. 摘要要求：准确描述本次改动，不写空话。
4. 若仅少量变更，也保持可读性与可检索性。

示例：

- `feat(site): 新增全站 head 广告脚本注入`
- `fix(i18n): 修正 relref 相关文章链接路径`
- `chore(content): 合并 AI 工作流分类到 AI工具`

## 错误处理

1. 若无可提交变更（nothing to commit），明确告知并停止 push。
2. 若 push 失败，先回报关键错误（权限、远端不存在、冲突等）。
3. 常见 SSH/权限问题可在用户确认后重试高权限环境。

## 输出约定

1. 汇报提交哈希、分支名、提交信息。
2. 汇报 push 结果（成功或失败原因）。
3. 仅在确有失败时提供下一步最小操作建议。

How to Check Whether an Ollama Model Is Loaded on GPU

Mon, 06 Apr 2026 10:15:18 +0800

If you want to confirm whether an Ollama model is actually running on GPU, the most direct way is checking processor allocation for currently loaded models.

Command

`1`	`ollama ps`

Example Output

1
2

NAME        ID            SIZE    PROCESSOR   UNTIL
llama3:70b  bcfb190ca3a7  42 GB   100% GPU    4 minutes from now

How to Read the `PROCESSOR` Column

100% GPU: The model is fully loaded into GPU VRAM.
100% CPU: The model is fully loaded in system memory (no GPU inference).
48%/52% CPU/GPU: The model is split between system memory and GPU VRAM.

Practical Tips

If you expect GPU usage but see 100% CPU, first check GPU drivers, CUDA/ROCm environment, and Ollama runtime settings.
With larger models and limited VRAM, CPU/GPU mixed loading is common.
For performance troubleshooting, run ollama ps before checking speed metrics to locate bottlenecks faster.

Summary

ollama ps is the first step to verify real GPU usage. Focus on the PROCESSOR column to quickly identify where the model is loaded and decide your next optimization action.

Using AI Agent Skills to Maintain a Hugo Multilingual Blog

Mon, 06 Apr 2026 10:00:00 +0800

If you maintain a Hugo multilingual blog, you probably run into a frequent pain point:

After finishing Chinese content, you still need synchronized English and Traditional Chinese versions
All language files must keep the same structure
Front matter must be translated while still following Hugo format rules

sync-post-translations is built for exactly this scenario.

What Problem This Skill Solves

The positioning of sync-post-translations is straightforward:

Use index.zh-cn.md as the source file
Generate or update index.en.md and index.zh-tw.md in the same directory
Keep Markdown structure consistent
Apply explicit front matter rules (especially date and slug)

Example trigger phrases:

“Sync translation to English and Traditional Chinese”
“Translate this post to English and Traditional Chinese”

Skill Directory Structure

.\sync-post-translations\
├─ SKILL.md
└─ agents\
   └─ openai.yaml

Core Code 1: SKILL.md

Below is the core rules file of this skill:

---
name: sync-post-translations
description: 将 Hugo 文章从简体中文源文件（`index.zh-cn.md`）同步翻译为英文（`index.en.md`）和繁体中文（`index.zh-tw.md`）。当用户提出“en 繁体”“同步翻译英文繁体”或要求同时生成/更新两种语言版本且需保持 front matter 与 Markdown 结构一致时使用。
---

# 同步文章翻译

使用此技能为同一篇文章生成或更新多语言版本。

## 工作流程

1. 在目标文章目录中定位源文件 `index.zh-cn.md`。
2. 读取完整 front matter 与正文内容。
3. 在同目录创建或更新 `index.en.md` 与 `index.zh-tw.md`。
4. 确保三语结构对齐后执行 Hugo 构建检查。

## 翻译规则

1. 严格保留 `slug` 原值。
2. `date` 统一规范为 Hugo 常用带时间格式（RFC3339），示例：`2026-04-05T10:00:00+08:00`。
3. 自然翻译以下 front matter 字段：`title`、`description`、`tags`、`categories`。
4. 保持 Markdown 结构不变：标题层级、列表形态、代码块、链接与命令行示例。
5. 技术标识符保持原样：文件名、CLI 参数、模型名、设备名、URL、包名等。
6. 若 YAML 的 `title` 含有 `:`，必须加引号，避免解析报错。
7. 在不改变语义前提下，使用目标语言自然标点与表达习惯（`en`、`zh-tw`）。

## 输出约定

1. 仅在源文章同目录写入目标文件。
2. 汇报变更的文件路径。
3. 条件允许时执行 `hugo --source . --destination public`，并反馈通过/失败；失败时给出关键报错行。

## 质量标准

1. 全文术语前后一致。
2. 避免机器直译感，优先可发布文风。
3. 章节内容完整，不省略示例、注意点与总结。

Core Code 2: agents/openai.yaml

This file defines how the skill is presented and prompted on the agent side:

interface:
  display_name: "同步文章翻译"
  short_description: "生成或更新 EN + ZH-TW 翻译稿"
  default_prompt: "使用该技能在同一 Hugo 文章目录中，从 `index.zh-cn.md` 生成或同步 `index.en.md` 与 `index.zh-tw.md`，保留 `date` 与 `slug`，保持 Markdown 结构一致，并执行 Hugo 构建校验。"

Practical Usage Example

1) Natural language trigger

1
2

请把 content/post/2026/04/06/index.zh-cn.md 同步翻译成英文和繁体，
要求 date 用 RFC3339，slug 不变，最后跑 hugo 校验。

2) Expected output

已更新：
- content/post/2026/04/06/index.en.md
- content/post/2026/04/06/index.zh-tw.md

构建校验：
- hugo --source . --destination public
- 结果：PASS

Why These Rules Matter

Keeping slug unchanged preserves stable URLs and historical backlinks.
Normalizing date to RFC3339 with timezone avoids Hugo/theme parsing ambiguity.
Keeping Markdown structure unchanged prevents TOC, code block, and shortcode rendering issues.
Not translating technical identifiers significantly reduces broken command/file mismatches.

Common Pitfalls and How to Avoid Them

If title contains : without quotes, YAML parsing can fail.
Translating --flags, URLs, or package names will break command examples.
If heading levels differ across languages (for example, ## becoming ###), anchors can become inconsistent.
Translating only body content but not front matter can break list pages and SEO metadata.

Ollama Default Model Storage Path and Migration Guide (Avoid Filling Up C Drive)

Mon, 06 Apr 2026 09:38:00 +0800

When running local LLMs, the system drive is often the first thing to run out of space. Ollama stores models in user or system directories by default, so your C drive can fill up quickly without path planning.

Common Default Ollama Model Directories

Windows: C:\Users\<username>\.ollama\models
macOS: ~/.ollama/models
Linux: /usr/share/ollama/.ollama/models (may vary by installation method)

Windows: Move the Model Directory to a Non-System Drive

A practical choice is moving model storage to a path like D:\OllamaModels. The key is setting the OLLAMA_MODELS system environment variable.

1. Create the Target Directory

For example, create: D:\OllamaModels

2. Configure the System Environment Variable

Variable name: OLLAMA_MODELS
Variable value: D:\OllamaModels

You can set it in “System Properties -> Advanced -> Environment Variables”, or with an admin PowerShell command:

`1`	`[System.Environment]::SetEnvironmentVariable("OLLAMA_MODELS", "D:\OllamaModels", "Machine")`

3. Restart Ollama (or Reboot the System)

After setting the variable, restart the Ollama service/app. If you’re unsure whether it has taken effect, rebooting the PC is the most reliable option.

4. Verify the New Path Is Active

Pull any model and check whether new files appear under D:\OllamaModels.

5. Clean Up the Old Directory (After Confirmation)

Once models work correctly in the new location, remove old files to reclaim C drive space.

FAQ

Still Writing to C Drive After Configuration

Confirm the variable is a system variable, not a temporary session variable.
Confirm the Ollama process was restarted.
Verify the variable name is exactly OLLAMA_MODELS.

Do I Need to Migrate Existing Model Files

If you want to avoid re-downloading, stop Ollama, copy existing model files to the new directory, then restart Ollama and verify.

Completely Uninstall Ollama on Linux (Including Leftover Cleanup)

Mon, 06 Apr 2026 09:16:29 +0800

If you need to remove Ollama completely from Linux, follow the steps below in order. This guide cleans up the service, executable, model directory, and the ollama user/group.

Before You Uninstall

The commands below will delete local Ollama model files (usually in /usr/share/ollama). Back up first if needed.
These commands use sudo by default. Make sure your account has administrator privileges.

1. Stop and Remove the systemd Service

sudo systemctl stop ollama
sudo systemctl disable ollama
sudo rm -f /etc/systemd/system/ollama.service
sudo systemctl daemon-reload

2. Remove the Ollama Binary

OLLAMA_BIN="$(command -v ollama)"
if [ -n "$OLLAMA_BIN" ]; then
  sudo rm -f "$OLLAMA_BIN"
fi

3. Remove Ollama Library Directories (If Present)

If your installation wrote Ollama files into a lib directory, clean them up with:

1
2
3

for d in /usr/local/lib/ollama /usr/lib/ollama /lib/ollama; do
  [ -d "$d" ] && sudo rm -rf "$d"
done

4. Remove Model and Data Directory

`1`	`sudo rm -rf /usr/share/ollama`

5. Remove System User and Group (If Present)

1
2

id -u ollama >/dev/null 2>&1 && sudo userdel ollama
getent group ollama >/dev/null 2>&1 && sudo groupdel ollama

6. Verify Uninstall Completion

1
2

command -v ollama || echo "ollama binary not found"
systemctl status ollama || true

If ollama is no longer found in the checks above, the uninstall is complete.

LLM Quantization Explained: How to Choose FP16, Q8, Q5, Q4, or Q2

Sun, 05 Apr 2026 22:09:11 +0800

The core goal of quantization is simple: trade a small amount of precision for a smaller model size, lower VRAM usage, and faster inference.
For local deployment, picking the right quantization format is often more important than chasing a larger parameter count.

What Is Quantization

Quantization means compressing model parameters from higher-precision formats (such as FP16) into lower-bit formats (such as Q8 and Q4).

A simple analogy:

Original model: like a high-quality photo, clear but large.
Quantized model: like a compressed photo, slightly less detail but lighter and faster.

Common Quantization Formats

Quantization	Precision / Bit Width	Size	Quality Loss	Recommended Use
FP16	16-bit float	Largest	Almost none	Research, evaluation, max quality
Q8_0	8-bit integer	Larger	Almost none	High-end PCs, quality + performance
Q5_K_M	5-bit mixed	Medium	Slight	Daily driver, balanced choice
Q4_K_M	4-bit mixed	Smaller	Acceptable	General default, strong value
Q3_K_M	3-bit mixed	Very small	Noticeable	Low-spec devices, run-first
Q2_K	2-bit mixed	Smallest	Significant	Extreme resource limits, fallback

Quantization Naming Rules

Take gemma-4:4b-q4_k_m as an example:

gemma-4:4b: model name and parameter scale.
q4: 4-bit quantization.
k: K-quants (an improved quantization method).
m: medium level (common options also include s/small and l/large).

Quick Selection by VRAM

RAM / VRAM	Recommended Quantization
4 GB	Q3_K_M / Q2_K
8 GB	Q4_K_M
16 GB	Q5_K_M / Q8_0
32 GB+	FP16 / Q8_0

Start with a version that runs stably on your machine, then move up in precision step by step instead of jumping straight to the biggest model.

Practical Tips

Start with Q4_K_M by default and test real tasks first.
If response quality is not enough, move up to Q5_K_M or Q8_0.
If VRAM or speed is the main bottleneck, move down to Q3_K_M.
Use the same test set every time you switch quantization formats.

Conclusion

Quality first: FP16 or Q8_0.
Balance first: Q5_K_M.
General default: Q4_K_M.
Low-spec fallback: Q3_K_M or Q2_K.

The key is not “bigger is always better”, but “the most stable and usable result under your hardware limits.”

Google Gemma 4 Model Comparison: How to Choose Between 2B/4B/26B/31B

Sun, 05 Apr 2026 08:30:00 +0800

Gemma 4 focuses on multimodality and local offline inference, with a full range from lightweight to high-performance models. For most local deployment users, the key is not choosing the largest model, but choosing the one that best matches hardware and task needs.

Gemma 4 Model Comparison

The table below is for quick model selection. Actual performance and resource usage should be validated in your own environment.

Model	Parameter Size	Positioning	Key Strengths	Main Limitations	Recommended Scenarios
Gemma 4 2B	2B	Ultra-lightweight	Low latency, low resource usage, lowest deployment barrier	Limited performance on complex reasoning and long task chains	Mobile, IoT, lightweight Q&A, simple automation
Gemma 4 4B	4B	Lightweight enhanced	Stronger understanding and generation than 2B, still easy to deploy locally	Limited ceiling for heavy coding and complex agent tasks	Local assistant, basic document work, multilingual daily tasks
Gemma 4 26B	26B	High-performance (MoE)	Better reasoning and tool use, suitable for production workflows	Significantly higher VRAM requirement and hardware threshold	Coding assistant, complex workflows, enterprise internal agents
Gemma 4 31B	31B	High-performance (dense)	Best overall capability and stronger stability on complex tasks	Highest resource cost and tuning complexity	Advanced reasoning, complex coding tasks, heavy automation

How to Choose: Start from Hardware and Tasks

If your top concern is whether it runs smoothly, use this guideline:

8GB VRAM: prioritize 2B/4B.
12GB VRAM: prioritize 4B or quantized variants of larger models.
24GB VRAM: focus on 26B, and evaluate quantized 31B based on workload.
Higher VRAM or multi-GPU: consider high-precision 31B setups.

Prioritize stability and inference speed first, then scale up model size gradually.

Four Typical Use Cases

1) Local General Assistant

Preferred model: 4B
Why: strong balance between cost and quality, suitable for long-running local use.

2) Coding and Automation

Preferred model: 26B
Why: more stable in multi-step tasks, tool calls, and script generation.

3) Advanced Reasoning and Complex Agents

Preferred model: 31B
Why: stronger robustness under complex context.

4) Edge Devices and Lightweight Offline Use

Preferred model: 2B
Why: easiest to deploy on resource-constrained devices.

Deployment Suggestions (Ollama)

A practical approach is to iterate in small steps:

Start with 4B to establish a baseline (latency, memory, quality).
Build a fixed test set from real tasks (for example, 20 common questions + 10 automation tasks).
Compare 26B/31B against that set for accuracy, latency, and VRAM cost.
Upgrade only when the gain is clear.

This avoids jumping to a large model too early and running into lag, low throughput, and maintenance overhead.

Conclusion

The real value of Gemma 4 is not just larger parameter counts, but a practical model ladder from lightweight to high-performance:

For low-cost fast rollout: start with 2B/4B.
For production-grade local AI workflows: prioritize 26B.
For advanced reasoning and heavy automation: move to 31B.

In most cases, the best Gemma 4 choice is not the biggest model, but the one with the best fit for your hardware and task goals.

Analyzing Anthropic's docx Agent Skill: Features, Code Structure, Usage, and Caveats

Sat, 04 Apr 2026 11:00:00 +0800

Anthropic’s skills/docx is essentially a workflow spec plus a script toolkit for handling Word documents more reliably with AI.
It does not just tell a model to “generate a .docx.” Instead, it breaks document work into explicit paths: create, read, edit existing files, handle tracked changes, add comments, convert formats, and validate OOXML structure.

If we reduce it to one line:

It treats .docx as ZIP + XML + Office compatibility constraints, not as a black box.

What this skill solves

When general-purpose models handle Word files, we often see the same failure patterns:

They output text, but not a structurally valid .docx.
They break OOXML while editing existing documents.
They do not know which XML parts to update for comments or tracked changes.
Output opens in one app but behaves inconsistently across Word, LibreOffice, and Google Docs.
They lack clear routing for when to use pandoc vs. unpack/edit/repack.

The value of this skill is that it front-loads those decisions:

Use pandoc or unpacking for reading and analysis.
Use docx-js for creating new .docx files.
Use “unpack -> edit XML -> repack -> validate” for existing documents.
Use dedicated scripts for tracked changes/comments/schema-sensitive operations.

That approach works because Word problems are usually not about wording quality. They are about structural correctness and compatibility.

Directory and code structure

This skill can be understood in four layers.

1. Guidance layer: `SKILL.md`

SKILL.md does two important jobs:

It defines trigger conditions.
If a request mentions Word, .docx, comments, tracked changes, TOC, page numbers, or polished document formatting, this skill should be activated.
It defines execution routes.
Different task types map to different toolchains, instead of improvising every run.

It also captures practical compatibility rules, for example:

docx-js defaults to A4, not US Letter.
Landscape page sizing must follow docx-js internals.
Lists should not be built from manual Unicode bullets.
Table width needs coordinated settings at table and cell levels.
Image type is required.
Generated files should be validated.

That is a strong signal that the goal is not just “generate something,” but “generate something that is robust.”

2. Office package layer: `scripts/office/*`

This layer treats .docx/.pptx/.xlsx as Open XML packages.

`unpack.py`

This script unpacks files and prepares XML for safer editing:

Extracts ZIP package content
Pretty-prints XML and .rels
Optionally runs merge_runs for DOCX
Optionally runs simplify_redlines for DOCX
Escapes smart quotes into XML entities

So it is not just decompression. It normalizes content into an editing-friendly shape.

`pack.py`

This script repacks a directory into .docx/.pptx/.xlsx.
Before packaging, it can:

Run validation and auto-repair
Condense XML formatting safely

If --original is provided, it compares and validates against the source context.
That matters because “repacked successfully” is not equal to “semantically safe.”

`validate.py`

This is the quality gate. It checks:

XML well-formedness
Namespace correctness
Unique ID constraints
Relationship/content type consistency
XSD compliance
Whitespace preservation rules
Insertion/deletion/comment marker constraints

For DOCX work, this is a core component, not an optional extra.

`soffice.py`

This helper wraps LibreOffice execution for restricted/sandboxed environments.
It configures SAL_USE_VCLPLUGIN=svp and can apply a shim for AF_UNIX socket limitations when needed.

That tells us the skill is designed for automated agent workflows, not only local manual usage.

3. Word-specific layer: comments, revisions, and redlines

`comment.py`

This script adds comments to DOCX, including required package plumbing across multiple parts:

word/comments.xml
commentsExtended.xml
commentsIds.xml
commentsExtensible.xml
comment range markers in document.xml
declarations in [Content_Types].xml and document.xml.rels

If comment parts do not exist yet, it can initialize templates and required relationships/content types.

`accept_changes.py`

This script accepts all tracked changes via LibreOffice headless + macro (.uno:AcceptAllTrackedChanges) rather than fragile raw XML surgery.

That is a pragmatic choice because accepting revisions is a behavior-level operation, not just deleting <w:ins> / <w:del> tags.

`validators/redlining.py`

This is one of the most valuable pieces.
It removes tracked changes for a specific author in both original and modified documents, then compares resulting text to verify that changes are properly represented in revision markup.

So it validates revision semantics, not only XML syntax.

4. Schema and support layer: `schemas/`, `helpers/`, `templates/`

`schemas/`

Contains OOXML/ECMA/Microsoft-related XSD files used by validators.
Validation is therefore grounded in formal schema constraints.

`helpers/`

Includes utilities such as:

merge_runs.py
simplify_redlines.py

These stabilize XML structure for clearer edits and diffs.

`templates/`

Contains XML templates needed for comment support, including:

comments.xml
commentsExtended.xml
commentsIds.xml
commentsExtensible.xml
people.xml

These templates help avoid package-level inconsistencies when creating comment-related parts.

Typical usage patterns

From SKILL.md, the most common workflows are:

Scenario 1: Read/analyze an existing DOCX

Use pandoc for text-level extraction with tracked changes:

`1`	`pandoc --track-changes=all document.docx -o output.md`

Use unpacking for raw XML inspection:

`1`	`python scripts/office/unpack.py document.docx unpacked/`

Scenario 2: Create a new DOCX

Use docx-js for generation:

`1`	`npm install -g docx`

Then validate:

`1`	`python scripts/office/validate.py doc.docx`

Scenario 3: Edit an existing DOCX

Core workflow:

1
2
3

python scripts/office/unpack.py document.docx unpacked/
# edit XML under unpacked/
python scripts/office/pack.py unpacked/ output.docx --original document.docx

--original is the critical part because it enables stronger structural and revision-aware checks.

Scenario 4: Accept all tracked changes

`1`	`python scripts/accept_changes.py input.docx output.docx`

Requires LibreOffice; useful for producing a clean post-review file.

Scenario 5: Add comments

1
2

python comment.py unpacked/ 0 "Comment text"
python comment.py unpacked/ 1 "Reply text" --parent 0

You still need to place comment range markers in document.xml where the comment should attach.

Key caveats to remember

1. `.docx` is not a plain text file

A single edit may involve body XML, relationships, content types, comment parts, IDs, and schema constraints.

2. `docx-js` generation still needs explicit guardrails

Defaults can be wrong for your target layout and compatibility goals.

3. Comments and tracked changes are multi-part operations

They are package-level features, not single-tag edits.

4. “Opens successfully” does not mean “correctly modified”

Many issues only surface later during editing, reviewing, cross-app opening, or acceptance of changes.

5. Environment readiness matters

You need tools such as pandoc, LibreOffice/soffice, docx-js, and Python deps (defusedxml, lxml) available.

What this skill is good for (and not)

Good fit

Batch Word report generation
Structured formal document production
Automated edits to existing .docx
Tracked-changes aware workflows
Automated comment insertion
Agent/script-driven document pipelines

Not ideal

Very simple PDF-only output cases
Pure text extraction with no document fidelity requirement
Fully manual visual editing workflows
Zero-dependency expectations for end-to-end Word automation

Summary

Anthropic’s skills/docx is strong not because it can “generate Word files,” but because it encodes why Word automation fails and how to handle those failure modes systematically.
It combines generation, low-level XML editing, revision semantics, schema validation, and cross-app compatibility into one executable workflow.

If your use case includes existing DOCX edits, comments, tracked changes, or compatibility-sensitive automation, this design is very practical and high value.

Code location: https://github.com/anthropics/skills/tree/main/skills/docx

Two Ways to Remotely Access Feiniu NAS and Their Comparison

Sat, 04 Apr 2026 11:00:00 +0800

There are two common ways to remotely access a Feiniu NAS:

Direct public IP access
FN Connect remote access service

Below is a practical guide organized by “how to use + key notes + best-fit scenarios.”

Option 1: Direct Public IP Access

This is suitable when your home network has a public IP and you can configure port forwarding on the router.
After that, you can access it by entering the public IPv4/IPv6 address and port in a browser or in the Feiniu App.
You can also set up DDNS and access via domain name.

Notes

Default ports for Feiniu private cloud fnOS: HTTP = 8000, HTTPS = 8001
If port forwarding is configured, the access URL must include the port number; otherwise, access will fail.
Direct public IP access usually has no extra relay, so speed loss is lower.
If security certificates are not configured properly, HTTP is plaintext. Use only in trusted network environments.
Many broadband providers block common ports such as 80 and 8080. If common ports do not work, try less common ports.

Option 2: FN Connect Remote Access Service

FN Connect is a remote-access service provided by Feiniu.
After enabling it, you get a unique FN ID to identify your Feiniu NAS and access it remotely through the corresponding method.

Notes

FN Connect requires you to register or sign in with a Feiniu account.
FN Connect provides an SSL certificate for the subdomain mapped to your FN ID, enabling secure HTTPS access.
FN Connect automatically chooses a better connection method based on your current network environment.
When direct public access is available, the web client can choose whether to use direct public IP access.
FN Connect relay forwarding has traffic cost, so rate limiting applies.

Comparison of the Two Methods

Dimension	Direct Public IP Access	FN Connect
Getting started	Requires public IP + router port forwarding	Lower barrier with account login and guided setup
Access speed	Usually faster with a more direct path	Close to direct mode when direct; possibly limited when relayed
Security	Depends on your own certificate and exposure strategy	Certificate support by default, easier HTTPS setup, depends on Feiniu’s own security
Maintenance cost	You maintain network and security settings yourself	Lower day-to-day maintenance effort
Best for	Users with networking experience and performance focus	Users who prioritize ease of use and stability

Recommendations

If you are comfortable with networking and want higher bandwidth/lower latency, prioritize direct public IP access.
If you care more about ease of use and secure access experience, prioritize FN Connect.
In practice, you can mix both: use FN Connect by default, and switch to direct public IP when conditions allow.

JMicron Chip Top Mark and Part Number Format

Sat, 04 Apr 2026 10:00:00 +0800

Each device has a unique top mark used to identify the vendor, device name, part number, manufacturing date code, lot number, and Pin 1 orientation.
The top-mark layout is shown below.

Part Number Format

The part number includes: vendor, product category, device number, package type, material type, product grade (operating temperature), Mask ROM version, and IC revision.
Its format can be written as J M B 5 8 5 - Q H B A 0 A, mapped to fields a b c d e f g h, and divided into Section I and Section II:

Section	Field	Characters	Meaning
Section I	a	`JM`	Brand name
Section I	b	`B`	Product category
Section I	c	`585`	Device number
Section II	d	`Q`	Package type
Section II	e	`H`	Material and grade
Section II	f	`B`	Internal bonding type
Section II	g	`A0`	Mask ROM version
Section II	h	`A`	IC revision

Field	Length	Definition	Code(s)	Notes
a (JM)	2 digits	Brand name	JM	Vendor is JMicron
b (B)	1 digit	Product category	B	`B = Bridge`, `S = SOC`
c (585)	3 digits	Device number	585	Combined with brand and category to form device name `JMB585`
d (Q)	1 digit	Package type	B, L, Q, T	`B = BGA`, `L = LQFP`, `Q = QFN`, `T = TQFP`
e (H)	1 digit	Material and grade	G, H, I, J	`G`: Gold wire, RoHS, halogen-free, Ta: 0 to 70°C; `H`: Copper wire, RoHS, halogen-free, Ta: 0 to 70°C `I`: Gold wire, RoHS, halogen-free, Ta: -40 to 85°C; `J`: Copper wire, RoHS, halogen-free, Ta: -40 to 85°C
f (B)	1 digit	Internal bonding type	A, B, C, …	Internal bonding code
g (A0)	2 digits	Mask ROM version	A0, A1, A2, …; B0, B1, B2, …; Z0	`A` means A-series version; `B` means B-series version; `Z0` means no Mask ROM
h (A)	1 digit	IC revision	A, B, C, …	IC version code

CH347 Resource Guide: Drivers, Tools, and SPI Flash Programming

Fri, 03 Apr 2026 10:00:00 +0800

This post summarizes the CH347 resources I use most often, with one goal: get you from setup to debugging/programming as quickly as possible.

If you are new to CH347, prepare your environment in this order:

Check the official product page first
Install the correct driver for your use case
Prepare an SPI Flash tool and verify connectivity

Official Entry

CH347 product page: https://www.wch.cn/products/CH347.html

It is best to download from the official page first, to avoid outdated or unknown-source driver packages.

Common Drivers

1) `CH341PAR.EXE`

Purpose:

USB-to-JTAG / SPI / I2C / Parallel / GPIO interface driver

Typical use:

Multi-protocol communication and low-level interface debugging with CH347

2) `CH343SER.EXE`

Purpose:

Vendor Windows driver for high-speed USB-to-Serial

Typical use:

Using CH347 mainly as a serial tool, especially at higher baud rates

SPI Flash Programming Tool

AsProgrammer: https://github.com/nofeletru/UsbAsp-flash

Common tasks:

Detect SPI NOR Flash
Read chip ID
Back up original firmware
Erase / write / verify firmware

Recommended Workflow (to avoid common mistakes)

After installing drivers, replug the device and confirm detection in Device Manager.
Before first write, do one full read + backup of the original contents.
Always run verify after writing. Do not rely only on a “write successful” message.
If the chip is not detected, check power, voltage level, and wiring before checking software settings.

Quick Troubleshooting

Device is plugged in but not visible in tools: usually driver loading issues, or a power-only USB cable.
Device is detected but read/write fails: first check wiring order, shared ground, and power stability.
Unstable behavior at high speed: lower read/write speed first, then increase gradually after stability is confirmed.

Summary

CH347 is not hard to use. The key is to get four things right: driver, tool, wiring, and verification.

The resources above cover most beginner and day-to-day maintenance scenarios, and should get you to a stable workflow quickly.

Automatically Renew Let's Encrypt Certificates on Ubuntu (Certbot + Nginx)

Fri, 03 Apr 2026 00:00:00 +0000

Let’s Encrypt certificates are valid for only 90 days, so production sites should always enable automatic renewal to avoid HTTPS downtime.

If you already issued the certificate with Certbot, there are usually two things left:

Configure a scheduled renewal task
Verify the renewal workflow actually works

First, Check Whether Certbot Already Created a Scheduler

Depending on your distro, Certbot may already install a scheduler (for example, a systemd timer or /etc/cron.d/certbot).

You can check with:

`1`	`systemctl list-timers \| grep certbot`

If a valid timer already exists, you usually do not need an extra crontab entry.

Add a Crontab Job Manually (Recommended Example)

If you prefer managing renewal explicitly, edit root crontab:

`1`	`sudo crontab -e`

Add this line (runs daily at 03:00):

`1`	`0 3 * * * certbot renew --pre-hook "systemctl stop nginx" --post-hook "systemctl start nginx" >> /tmp/certbot-renew.log 2>&1`

What it means:

0 3 * * *: run at 03:00 every day
certbot renew: renew certificates that are close to expiration
--pre-hook: stop Nginx before renewal (common for standalone mode)
--post-hook: start Nginx after renewal
>> /tmp/certbot-renew.log 2>&1: append logs for troubleshooting

Run a Dry Test Before Relying on Cron

After adding the task, validate the full flow manually:

`1`	`sudo certbot renew --dry-run`

If dry-run succeeds, you can safely rely on the scheduled job.

Common Notes

If you use the webroot or nginx plugin, you often do not need to stop Nginx. In many setups, reloading Nginx after renewal is enough:

`1`	`certbot renew --deploy-hook "systemctl reload nginx"`

certbot renew only performs actual renewal near expiration, so running it daily is normal.
For long-term maintenance, consider writing logs to a persistent path such as /var/log/letsencrypt/.

Summary

Reliable certificate auto-renewal is not just about writing a command. The key is confirming the workflow can run end to end.

A stable setup is usually just these three steps:

Check whether system-level scheduling already exists
Add cron if needed and keep logs
Validate once with --dry-run

FFmpeg `-map` Explained: Precisely Select Video, Audio, and Subtitle Streams

Thu, 02 Apr 2026 23:14:03 +0800

In multi-audio and multi-subtitle workflows, -map is one of FFmpeg’s most important and most frequently misused options.

If you don’t explicitly specify -map, FFmpeg auto-selects streams using default rules, and the output is often not what you expect. For example:

Subtitles disappear after export
The wrong language track is selected
Unwanted data streams are included

This article uses common real-world scenarios to explain how -map works.

First, Understand What a “Stream” Is

A container file (such as mp4 or mkv) usually contains multiple streams, including:

Video streams (v)
Audio streams (a)
Subtitle streams (s)
Attachment/data streams (fonts, cover art, chapters, etc.)

You can inspect streams with ffprobe:

`1`	`ffprobe -hide_banner input.mkv`

Basic `-map` Syntax

Most common pattern:

`1`	`-map input_index[:stream_type][:stream_index]`

Examples:

0:v: all video streams from the 1st input
0:a:0: the 1st audio stream from the 1st input
1:s:1: the 2nd subtitle stream from the 2nd input

Notes:

input_index starts from 0, based on -i order
stream_index also starts from 0

Practical Examples

1) Video from A, audio from B

ffmpeg -i english.mp4 -i french.mp3 \
  -map 0:v:0 -map 1:a:0 \
  -c:v copy -c:a aac \
  french.mp4

Meaning:

Use the first video stream from english.mp4
Use the first audio stream from french.mp3
Merge into french.mp4

2) Keep all streams from input 1, then add one more audio track

ffmpeg -i english.mp4 -i french.mp3 \
  -map 0 -map 1:a:0 \
  -c copy \
  english-french.mp4

Meaning:

-map 0 keeps all streams from the first input
Then append the first audio stream from the second input

Two Useful Advanced Tricks

1) Negative mapping: exclude unwanted streams

For example, keep everything from input 1 but remove its second audio stream:

`1`	`ffmpeg -i input.mkv -map 0 -map -0:a:1 -c copy output.mkv`

2) Optional mapping: don’t fail when a stream is missing

If some files may not have subtitles, use ?:

`1`	`ffmpeg -i input.mp4 -map 0:v -map 0:a -map 0:s? -c copy output.mp4`

0:s? means: map subtitles if present; otherwise skip without error.

Common Pitfalls

Once you use -map, FFmpeg stops automatic stream selection, so you must map everything you need.
-c copy only remuxes without transcoding. If the target container doesn’t support a codec, it still fails.
With multiple inputs, index mistakes are common. Input indices are determined only by -i order.
For robust scripts, inspect with ffprobe first, then generate -map dynamically.

Summary

The core idea of -map is simple: explicitly tell FFmpeg which input to use, what stream type to pick, and which stream index to select.

Once you master this, you can reliably handle complex cases like multi-audio, multi-subtitle, and cross-file stream composition.

Home Printer Buying Guide

Wed, 01 Apr 2026 00:00:00 +0000

The biggest mistake when buying a home printer is usually not “low specs” but choosing a model that does not match your daily usage.

This guide avoids jargon and focuses on four factors that matter most in real-world use, so you can pick a printer that stays useful over time.

Laser or Inkjet

Start with a simple rule of thumb:

If you mainly print black-and-white documents with steady volume, prioritize laser
If you need color graphics, photos, or craft/school materials, prioritize inkjet

The biggest issue with inkjet printers is that printheads can clog after long periods of inactivity. Their advantage is better photo output and generally stronger color performance.
Laser printers are fast, sharp for text, and typically easier to maintain long term. The trade-off is that color laser models and supplies are usually more expensive.
If your main use case is “black-and-white homework + documents,” a mono laser all-in-one is often the safer choice.

Wi-Fi, Ethernet, or USB?

Connectivity has a direct impact on everyday convenience:

USB: best for one fixed computer; simple and stable, but sharing across devices requires extra setup
Wi-Fi: easiest for home use across phones, tablets, and laptops
Ethernet: ideal for multi-user households or small studios that want stable shared access

Most homes now print from multiple devices, especially phones and tablets.
If you want the easiest setup path, choose a model with Wi-Fi.
Ethernet connected to your router can also provide stable shared printing; USB sharing is possible (for example via a print server or OpenWrt), but setup is usually more complex.

Automatic Duplex or Single-Sided?

Automatic duplex printing is easy to overlook, but highly practical.

It saves paper and removes manual page flipping when printing long documents. For families that regularly print study materials, worksheets, or contracts, this feature is well worth it.

If you only print 1 to 3 pages occasionally, single-sided models can still work. But over time, duplex support usually delivers a better experience.

Paper Tray Considerations

Paper tray design directly affects how often you need to intervene.

Focus on two points:

Closed tray or not: closed trays are better for dust and humidity control
Capacity: small trays are often around 100-200 sheets; larger trays are commonly 500 sheets and can hold a full ream

If you print frequently for school or work, a higher-capacity tray can noticeably reduce refill interruptions.

Summary

The best home printer is not the one with the highest specs, but the one that best matches your actual usage.
Decide whether your priority is documents or color output first, then filter by connectivity, duplex support, and tray capacity to avoid most buying mistakes.

How to Troubleshoot High VS Code CPU Usage Caused by Extensions

Wed, 01 Apr 2026 00:00:00 +0000

When VS Code suddenly feels laggy, your fan spins up, and CPU usage stays high, the most common cause is usually not the editor itself, but extension conflicts or abnormal extension behavior.

This guide gives you a direct, actionable workflow to identify the issue quickly.

Start with the Fastest Method: Start Extension Bisect

Start Extension Bisect uses a binary search approach: in each round, VS Code temporarily disables half of your extensions and restarts. Based on whether the issue still appears, it narrows down the suspect list quickly.

Steps:

Press Ctrl+Shift+P (macOS: Cmd+Shift+P) to open the Command Palette.
Run Start Extension Bisect.
After each restart, check whether high CPU usage and lag are still present, then choose Good now or This is bad.
After several rounds, VS Code will show the likely problematic extension(s).

What to Do After You Find the Suspect

Once you identify the extension, handle it in this order:

Update the extension to the latest version.
If the issue remains, disable it for 1-2 days and observe.
If alternatives exist, switch to a lighter extension.
If you must keep it, review advanced settings and disable unnecessary real-time analysis, indexing, or file watching features.

Two Common “Amplifiers” You Might Overlook

Even if an extension is the root cause, these settings can amplify CPU load:

Search scope is too broad
If build output, dependency folders, and logs are included in global search, extensions and indexers may stay under continuous heavy load.
File watching includes huge folders or symlinks
Symlinks, cache directories, and generated folders can trigger large numbers of file events and force extensions to reprocess repeatedly.

You can trim scope in settings.json, for example:

{
  "search.exclude": {
    "**/node_modules": true,
    "**/dist": true,
    "**/build": true
  },
  "files.watcherExclude": {
    "**/.git/objects/**": true,
    "**/node_modules/**": true,
    "**/dist/**": true
  }
}

Postmortem Tip

After isolating the issue, record three things: extension name, trigger scenario, and final fix.
That note will save time when you migrate your environment or rebuild your machine later.

Summary

For high VS Code CPU usage, the most effective path is to use Start Extension Bisect first, then tighten search and file watching scope.
Locate first, optimize second. It is faster and more reliable than randomly disabling many extensions.

rsync --delete Explained and Practical Directory Cleanup

Sun, 29 Mar 2026 11:00:00 +0800

The core purpose of rsync --delete is to remove files in the target directory that do not exist in the source directory, so both sides stay consistent.

Typical use cases include:

Cleaning stale files on the target side during sync
Quickly emptying a target directory by syncing from an empty source directory

Basic Syntax

`1`	`rsync -a --delete source_dir/ target_dir/`

-a: archive mode, preserves permissions, timestamps, and other attributes
--delete: removes extra files on the target side

Important note: whether source_dir ends with / changes behavior. With /, rsync syncs directory contents; without /, it syncs the directory itself.

Quickly Empty a Target Directory with an Empty Source

If your goal is to keep the directory path but clear all contents, use an empty directory as the source:

# 1) Create an empty directory
mkdir -p /tmp/empty_dir

# 2) Sync and delete target-side content
rsync -a --delete /tmp/empty_dir/ /path/to/target_dir/

In large-directory scenarios, this is often more efficient than deleting files one by one, and it is easier to automate in scripts.

Common Extended Options

--delete-before: delete before transfer, which can be faster in some cases
--progress: show transfer and processing progress

Example (cleaning an Nginx log directory):

`1`	`rsync -a --delete --progress /tmp/empty_dir/ /var/log/nginx/`

Recommendations

Run with --dry-run first to verify the deletion scope
Back up the target directory before running in production
For critical paths, schedule execution during off-peak hours

How Git Tracks File Executable Permission (+x)

Sun, 29 Mar 2026 10:00:00 +0800

In a Linux environment, Git tracks a file’s executable bit (+x). If you want a script to be preserved as an executable file in the repository, you need to explicitly record that permission change in Git.

Add Executable Permission to a File

1
2
3

git update-index --chmod=+x script.sh
git commit -m "chore: mark script.sh as executable"
git push

This command stages the executable-bit change for script.sh. After you commit and push, other users will keep the same permission state when they pull or clone the repository.

Remove Executable Permission from a File

1
2
3

git update-index --chmod=-x script.sh
git commit -m "chore: remove executable bit from script.sh"
git push

Verify the Result

Use the following commands to check file permissions in your working tree:

1
2

git clone xxxxxxxxxxxxxxx
ls -l script.sh

If you see something like -rwxr-xr-x, the file is executable. If you see -rw-r--r--, it is not executable.

Notes

git update-index --chmod=+x/-x only updates the file mode recorded by Git; it does not replace changes to file content.
In team workflows, it is best to commit permission-only changes separately for easier review and tracking.

Hugo Shortcode Practice: bundle-file (Keep Multilingual Files and Attachments in One Page Bundle)

Sun, 29 Mar 2026 00:00:00 +0000

In multilingual sites, posts often share the same attachment files (for example, PDFs, config files, or scripts). If each language version maintains download links manually, link drift and missing files become common over time.

This article introduces a reusable Hugo shortcode, bundle-file, to solve this problem.

Goal

Keep multilingual post files and attachments in the same Page Bundle directory, for example:

content/post/2026/03/09/01/
  index.zh-cn.md
  index.zh-tw.md
  index.en.md
  demo.pdf
  script.sh

This maximizes reuse and avoids duplicate copies. After Hugo builds HTML pages, all language versions should point to the same attachment instead of duplicated files.

Shortcode Implementation

File: layouts/shortcodes/bundle-file.html

{{- $name := .Get "name" -}}
{{- $text := .Get "text" | default $name -}}

{{- $res := .Page.Resources.GetMatch $name -}}
{{- if not $res -}}
  {{- range .Page.AllTranslations -}}
    {{- if not $res -}}
      {{- $tmp := .Resources.GetMatch $name -}}
      {{- if $tmp }}{{ $res = $tmp }}{{ end -}}
    {{- end -}}
  {{- end -}}
{{- end -}}

{{- if $res -}}
<a href="{{ $res.RelPermalink }}">{{ $text }}</a>
{{- else -}}
<span>Missing file: {{ $name }}</span>
{{- end -}}

bundle-file works with a simple strategy:

Look up the file in current page resources first.
If not found, search the same file name in other translated pages.
Output a download link when found, or show a missing-file message when not found.

Parameters

name: attachment filename (required)
text: link label (optional); defaults to name

Usage Example

`1`	`Missing file: demo.pdf`

Without text:

`1`	`Missing file: demo.pdf`

Pre-publish Checklist

Put attachments and post files in the same Page Bundle.
Ensure name exactly matches the real filename (including case).
Click links in local preview to confirm accessibility.

Summary

bundle-file turns multilingual attachment handling from manual path maintenance into rule-based automatic lookup. For long-lived knowledge bases and technical blogs, this reduces broken-link risk and pre-release review time.

How to Create and Use Skills: SKILL.md Specification and Practical Principles

Sat, 28 Mar 2026 16:30:00 +0800

This article focuses on two questions:

How should SKILL.md be written and structured?
How do we create high-quality, maintainable, reusable Skills?

1. SKILL.md Specification

SKILL.md is the core description file of a skill. It usually contains two parts:

YAML front matter: defines skill metadata.
Markdown body: defines execution guidance and practical workflow.

1.1 Front Matter Example

---
# === Required fields ===
name: skill-name
# Unique skill identifier; kebab-case is recommended

description: >
  Brief but precise description of:
  1) What this skill does
  2) When it should be used
  3) What its core value is
# Note: description is typically the key basis for skill selection

# === Optional fields ===
version: 1.0.0
allowed_tools: [tool1, tool2]
required_context: [context_item1]
license: MIT
author: Your Name <email@example.com>
tags: [database, analysis, sql]
---

1.2 Recommended Body Structure

# Skill Title

## Overview
(Skill summary, use cases, technical background)

## Prerequisites
(Runtime environment, dependencies, required permissions)

## Workflow
(Step-by-step guidance: input, process, output)

## Best Practices
(Experience-based tips, caveats, common pitfalls)

## Examples
(Typical cases for faster adoption)

## Troubleshooting
(Common issues and fixes)

2. Principles for Writing High-Quality Skills

Based on official documentation and community practice, the following four principles are recommended.

2.1 Keep Description Precise

description is the key entry point for skill matching. It should:

Clearly define scope; avoid vague wording like “helps with data processing.”
Include trigger keywords to match user intent.
Explain unique value and boundaries from other skills.

Weak example:

`1`	`description: Handle database queries`

Stronger example:

description: >
  Convert Chinese business questions into SQL queries and analyze the MySQL employees sample database.
  Suitable for employee info lookup, salary statistics, department analysis, and role-change history.
  Use this skill when users ask about employee, salary, or department data.

2.2 Modular Design and Single Responsibility

A skill should focus on one clearly defined task domain. If a single skill tries to cover too much, it often leads to:

Broader descriptions and lower matching precision.
Longer instructions and heavier context load.
Higher maintenance and iteration costs.

Instead of one “general analysis” skill, split into specialized skills, for example:

mysql-employees-analysis
sales-data-analysis
user-behavior-analysis

2.3 Determinism First

For complex tasks requiring precision, prefer scripted execution over pure LLM generation.

For example, in data export scenarios, instead of generating Excel binary content directly with an LLM, use a dedicated script. SKILL.md should only define when and how to invoke it.

2.4 Progressive Disclosure

Layer information by importance and frequency to reduce unnecessary context usage:

SKILL.md body: core workflow and common patterns
Supplementary docs (for example, advanced.md): advanced usage and edge cases
Data files: large reference data accessed on demand via scripts

Summary

The goal of high-quality Skills is not writing more, but writing clearer boundaries, better triggers, stable execution, and sustainable maintenance.

Start with a standardized SKILL.md, then combine single responsibility with progressive disclosure to build a more efficient skill system.

IEEE 802.3af/at/bt (PoE) Differences Explained

Sat, 28 Mar 2026 00:00:00 +0000

IEEE 802.3af, 802.3at, and 802.3bt are the three mainstream PoE (Power over Ethernet) standards. Their key differences are power budget, number of wire pairs used for power delivery, and target device types.

Quick Takeaways

802.3af (PoE): Lower maximum power (15.4W), suitable for basic devices.
802.3at (PoE+): Increased power up to 30W, suitable for medium-power devices.
802.3bt (PoE++ / 4PPoE): Highest power level (Type 3 up to 60W, Type 4 up to 90W-100W), suitable for high-power devices.

Detailed Comparison

Standard	Common Name	Max PSE Output	Usable PD Power (Approx.)	Powered Pairs	Typical Use Cases
IEEE 802.3af	PoE	15.4W	12.95W	2 pairs	Standard VoIP phones, basic cameras
IEEE 802.3at	PoE+	30W	25.5W	2 pairs	HD IP cameras, advanced network endpoints
IEEE 802.3bt	PoE++ / 4PPoE	Type 3: 60W; Type 4: 90W-100W	Higher (depends on type)	4 pairs	Wi-Fi 6/6E APs, video conferencing endpoints, building automation

Standard-by-Standard Notes

IEEE 802.3af (PoE)

Max output power: 15.4W (about 12.95W available at PD)
Pair usage: 2 out of 4 twisted pairs
Typical scenarios: legacy cameras, standard VoIP phones

IEEE 802.3at (PoE+)

Max output power: 30W (about 25.5W available at PD)
Pair usage: 2 out of 4 twisted pairs
Typical scenarios: HD IP cameras, higher-end network surveillance endpoints

IEEE 802.3bt (PoE++ / 4PPoE)

Max output power: up to 60W for Type 3, up to 90W-100W for Type 4
Pair usage: all 4 pairs for power delivery, enabling higher power capacity
Typical scenarios: high-power wireless APs, building automation, video conferencing systems

Compatibility

All three standards are backward compatible:

802.3bt is compatible with 802.3at and 802.3af
802.3at is compatible with 802.3af

As standards evolve, available power increases significantly, supporting a wider range of high-power terminal devices.

What Is Agent Skills: From Design Principles to Context Optimization

Sat, 28 Mar 2026 00:00:00 +0000

Agent Skills is a standardized way to package procedural knowledge. In short, it answers not only “whether tools exist” but “how to use them correctly and effectively.”

1. Core Design Principles

The core value of Agent Skills is that it captures reusable methodology:

It provides domain knowledge to guide how agents combine and invoke tools in specific scenarios.
It constrains execution paths, reducing trial-and-error and improving consistency.
It makes complex workflows reusable and iterative, forming stable SOPs over time.

If tool capability is like a hardware interface, Skills is closer to an operations manual plus best-practice playbook, defining what should be done and how.

2. Progressive Disclosure: Solving the Context Bottleneck

The key innovation in Agent Skills is Progressive Disclosure: load information only when needed, instead of pushing everything into the context window at once.

2.1 Layer 1: Metadata

Each skill is usually stored in its own folder, with SKILL.md as the core file. This file starts with YAML front matter that defines basic skill information.

At startup, the agent reads only the front matter of all skills and injects that metadata into the system prompt. In practice:

Metadata for one skill costs about 100 tokens
50 skills cost about 5,000 tokens

2.2 Layer 2: Instructions

When a skill is judged highly relevant to the current task, the agent then reads the full SKILL.md, loading detailed instructions, notes, and examples.

Token usage at this layer depends on instruction complexity, typically:

1,000 to 5,000 tokens

2.3 Layer 3: Additional Resources (Scripts & References)

For more complex skills, SKILL.md can reference scripts, config files, and docs, which are loaded only when needed.

Example directory structure:

skills/pdf-processing/
├── SKILL.md                 # Main skill file
├── parse_pdf.py             # PDF parsing script
├── forms.md                 # Form-filling guide (loaded only for form tasks)
└── templates/
    ├── invoice.pdf
    └── report.pdf

Typical invocation pattern:

Run parse_pdf.py when PDF parsing is required
Load forms.md only for form-filling tasks
Access template files only when generating specific output formats

3. Why This Design Works

3.1 Scalable Knowledge Capacity

With scripts and external files, a skill can carry knowledge far beyond context-window limits. For example, a data-analysis skill can include a 1GB dataset plus query scripts, and the agent can access data through execution instead of loading the whole dataset into context.

3.2 Stronger Determinism

Delegating complex computation, data transformation, and format parsing to code significantly reduces uncertainty and hallucination risk in pure text generation.

4. Practical Impact: From 16k to 500 Tokens

Community practice shows that Progressive Disclosure can drastically reduce initial context overhead:

Traditional MCP approach: directly connect to an MCP server with many tool definitions, around 16,000 tokens at initialization
With Skills packaging: use a lightweight gateway skill described mainly in front matter, around 500 tokens at initialization

Detailed instructions and additional resources are loaded only when the task truly requires them. This lowers initial cost and improves context management precision during the conversation.

Summary

The key value of Agent Skills is upgrading from “tools are available” to “capabilities are reusable.” With Progressive Disclosure, systems can preserve capability depth while significantly optimizing token cost and execution stability.

Common Misconceptions About WD HC620 SMR Drives and How to Use Them Correctly

Fri, 27 Mar 2026 00:00:00 +0000

Introduction: A New Option Under Soaring Storage Costs

The storage market is going through an unprecedented price surge, and storage costs have risen sharply for regular consumers and home NAS users. Large-capacity HDDs that once cost under 1,000 CNY now often cost two times more or even higher, putting them out of reach for many budget-conscious users. In this market environment, however, the HC620 is one of the few products that has not increased in price as dramatically. This article is not only about the HC620; it also applies to other similar SMR drives.

Common Misconceptions About HC620

Many people worry about whether HC620 is safe for data storage, but this is a typical misconception. The HC620 itself is an enterprise-grade drive, and its hardware quality is not poor. The “unsafe” impression usually comes from misunderstandings about SMR drives and using them in the wrong scenarios. SMR drives should not be used for frequent write-and-delete workloads, because that can trigger data reshuffling, reduce performance, and even cause severe stalls. But that is a workload mismatch, not a product defect. It is similar to enterprise tape systems: they work fine when used for sequential write and sequential read. Likewise, HC620 is suitable for sequential writes with random reads, but not for heavy concurrent delete-and-write workloads. In the right scenario, HC620 performs very well.

Suitable and Unsuitable Scenarios

Suitable scenarios:

Cold data backup and archiving at large capacity
Media libraries that are written once and then searched/read online (reads are naturally random head seeks, not strict sequential reads)

Unsuitable scenarios:

Workloads with frequent reads and writes (databases, downloading, active workspaces)
Direct usage on operating systems such as Windows and macOS is not supported (network-based access is excluded from this limitation)

Usage Requirements for HC620

The biggest issue with HC620 is convenience: it can be difficult to use, especially for beginners.

Hardware requirements

Do not connect it through a USB drive enclosure.
Direct connection to a motherboard SATA port is usually fine, but expansion cards can be inconsistent. Compatibility issues may occur. LSI 9300 (SAS3008) can work after flashing IT/HBA firmware. JMB585 has both working and non-working cases, so compatibility is mixed.
M.2-to-SATA adapters are also inconsistent. My M.2-to-JMB585 adapter works, but I have seen many incompatible cases, likely related to BIOS or firmware differences.

Software requirements

Not supported on Windows and macOS; supported on Linux
Supported on Feiniu NAS

Summary

For beginners, the easiest approach is to use Feiniu NAS and mount HC620 as external storage, using the whole drive for backups or a media library.

For users whose NAS capacity is full, moving less frequently used data to HC620 is also a practical way to free up NAS space.

How Non-Programmers Can Direct AI to Do the Work: Extracting Diagrams and Math Formulas from an Image (Hands-On Example)

Thu, 26 Mar 2026 00:00:00 +0000

Prerequisites

Install VS Code and the Codex extension. You can refer to this article.
Using these tools does not require programming experience. In this workflow, VS Code is mainly for organizing files; you describe your goal, and AI writes and runs the code for you.
This post records the full process to spark ideas and help more people discover practical ways to use AI.

Goal

Prepare an image that contains both math formulas and illustrative diagrams:

We want to achieve three things:

Split diagrams into clean, separate images.
Recognize formulas and convert them to LaTeX for easier editing.
Link each diagram to its corresponding formula.

Process

First, recognize the image, generate a Markdown document, and convert formulas to LaTeX

Conversion result:

# 1.png Recognition Result

## Geometry Formulas (LaTeX)

1. Triangle area (side lengths and circumradius):

$$
S = \frac{abc}{4R}
$$

2. Triangle area (inradius and semiperimeter):

$$
S = pr
$$

3. Frustum volume:

$$
V = \frac{\pi\left(r^2 + Rr + R^2\right)h}{3}
$$

4. Frustum lateral surface area:

$$
S = \pi a(R + r)
$$

5. Cylinder volume:

$$
V = \pi r^2 h
$$

6. Cylinder lateral surface area:

$$
S = 2\pi rh
$$

7. Sphere volume:

$$
V = \frac{4}{3}\pi R^3
$$

8. Sphere surface area:

$$
S = 4\pi R^2
$$

9. Law of sines:

$$
\frac{a}{\sin A}=\frac{b}{\sin B}=\frac{c}{\sin C}=2R
$$

10. Law of cosines:

$$
a^2=b^2+c^2-2bc\cos A
$$

$$
b^2=a^2+c^2-2ac\cos B
$$

$$
c^2=a^2+b^2-2ab\cos C
$$

All formulas were recognized, and AI even added formula names automatically, which is great. However, the small diagram crops were not generated yet.

Try asking AI to crop the image

# 1.png Recognition Result (side-by-side layout with refined cropping)

<table>
  <tr>
    <td>![](crops/01_triangle_circum.png)</td>
    <td>

$$
S = \frac{abc}{4R}
$$

</td>
  </tr>
  <tr>
    <td>![](crops/02_triangle_incircle.png)</td>
    <td>

$$
S = pr
$$

</td>
  </tr>
  <tr>
    <td>![](crops/03_frustum.png)</td>
    <td>

$$
V = \frac{\pi\left(r^2 + Rr + R^2\right)h}{3}
$$

$$
S = \pi a(R + r)
$$

</td>
  </tr>
  <tr>
    <td>![](crops/04_cylinder.png)</td>
    <td>

$$
V = \pi r^2 h
$$

$$
S = 2\pi rh
$$

</td>
  </tr>
  <tr>
    <td>![](crops/05_sphere.png)</td>
    <td>

$$
V = \frac{4}{3}\pi R^3
$$

$$
S = 4\pi R^2
$$

</td>
  </tr>
  <tr>
    <td>![](crops/06_laws.png)</td>
    <td>

$$
\frac{a}{\sin A}=\frac{b}{\sin B}=\frac{c}{\sin C}=2R
$$

$$
a^2=b^2+c^2-2bc\cos A
$$

$$
b^2=a^2+c^2-2ac\cos B
$$

$$
c^2=a^2+b^2-2ab\cos C
$$

</td>
  </tr>
</table>

Result: The diagrams were cropped and placed in matching positions, but the crops still include noise from nearby areas.

Fix over-cropping: keep the full target area first, then manually remove extra parts
The output is still inconsistent at this step. It is not yet clear whether the issue comes from prompting or model variability in visual localization.

Summary

Using Codex feels different from chatting directly on chatgpt.com.
On chatgpt.com, it often feels like AI is guiding your work; in Codex, it feels more like AI is executing your instructions.
After you describe your requirement, AI can generate code, run it, and complete the task. The feeling is that you are directing AI to do the work.
This process does not require strong programming skills, and non-programmers can still get real results step by step.

How to Use Codex in VS Code (From Setup to Efficient Real-World Workflow)

Fri, 20 Mar 2026 00:00:00 +0000

Codex can help you write code, fix bugs, understand projects, and run commands directly from the VS Code sidebar.

1. Preparation

Before you start, make sure:

VS Code is updated to a recent stable version.
You can access OpenAI services normally.
Your project is opened locally (preferably in a Git repository).

2. Install the Extension

Open the VS Code Extensions panel.
Search and install: Codex - Codex - OpenAI's coding agent.
Complete the sign-in/authorization flow.

You can open it in either way:

Click Open Codex Sidebar in the top-right area of the editor.
Use Command Palette (Ctrl + Shift + P), search Codex, and open it.

After opening, Codex reads the current workspace context and becomes ready for chat.

4. Common Usage Patterns

4.1 Ask It to Explain Code

Example prompt:

1
2

Please explain the core logic of this file,
and point out the 3 areas most likely to fail.

Great for quickly understanding legacy code.

4.2 Ask It to Implement Features

Example prompt:

1
2
3

Add a /healthz endpoint to the existing API.
It should return app version and database connectivity status,
and include basic tests.

If you clearly state constraints and acceptance criteria, output quality is usually much more stable.

4.3 Ask It to Fix Issues

Example prompt:

1
2
3

This endpoint intermittently returns 500 under concurrency.
First identify the root cause, then propose a minimal-change fix,
and finally list regression test points.

“Diagnose first, then fix” helps reduce accidental over-refactoring.

5. High-Quality Prompt Template

You can reuse this template directly:

Background: This is a <tech stack> project. Current goal: <goal>
Constraints: Do not modify <module/interface>; keep compatibility with <version/platform>
Output:
1) File list to change
2) Key code explanation
3) Validation steps
4) Risks and rollback plan

This is especially useful for large projects and team collaboration.

6. FAQ

6.1 About Free Quota

Type \ in the input box, then choose status to view quota/reset-time related information.

6.2 Changes Are Not as Expected

After changes are generated, open the review panel to inspect details. If not satisfied, use undo/revert. You can split large requirements into smaller steps and execute incrementally. Use Git and keep small commits for easier rollback.

LLM API Landscape (Free and Cost-Effective Options)

Thu, 12 Feb 2026 00:00:00 +0000

Google Gemini API (Best Free Tier)

To promote the Gemini lineup, Google currently provides one of the most generous free quotas. Pricing/details: https://ai.google.dev/gemini-api/docs/pricing?hl=zh-cn

Models: Gemini 3 Flash Preview, Gemini 2.5 Pro (as of 2026-02-12). In general, the newest top-end Pro model may have tighter free limits, while many other models still provide free usage.

Pros:

Even top-tier models may include free quota.
Very large context window (1M+ tokens).
Strong multimodal support (image/video input).

Cons:

Data privacy: free-tier inputs may be used by Google to improve models (use with caution in production).
IP restrictions: strict regional policy; unsupported locations may hit 403 or User Location Not Supported.

Groq (Speed King)

Groq uses its self-developed LPU (Language Processing Unit) hardware and provides extremely fast inference. Pricing/details: https://groq.com/pricing

Models: GPT OSS / Kimi K2 / Llama 3,4 / Qwen3 Quota: No free tier, but relatively low price.

Pros:

Very low latency; TTFT is often within 200ms.
Great for real-time chat and voice assistants.

Cons:

Model scope is mostly open-source models; no GPT-4 or Claude hosted directly.

SiliconCloud (Strong Domestic Option)

A fast-growing China-based inference platform that aggregates many high-quality domestic open-source models. Pricing/details: https://siliconflow.cn/pricing

Models: Qwen 2.5 (7B/14B/72B), DeepSeek-V2, Yi-1.5, Kimi K2. Quota: Some models (for example Qwen 7B, GLM-4-9B) currently offer permanent free calls.

Pros:

Fast domestic connectivity.
New domestic open-source models are usually available quickly.

Cons:

Free access is mainly for smaller models.
Top models (such as 72B / DeepSeek 236B) are usually paid.

OpenWrt on JDCloud AX6600 Athena: Move the 2.5G Port to LAN and Swap WAN/LAN1

Mon, 19 Jan 2026 00:00:00 +0000

Introduction

The JDCloud Wireless Treasure AX6600 Athena has a 2.5G port. In LEDE/libwrt builds of OpenWrt, this port is usually configured as WAN by default. In many home-lab scenarios, it is more useful as an internal LAN port for connecting NAS and other local servers. This article shows one practical DTS-based approach.

Method

OpenWrt’s web UI usually cannot directly remap this WAN/LAN assignment. You can do it by editing the DTS file.

Swap lan1 and wan:

Before:
	switch_lan_bmp = <(ESS_PORT1 | ESS_PORT2 | ESS_PORT3 | ESS_PORT4)>;
	switch_wan_bmp = <ESS_PORT5>;
  ...
  &dp1 {
	status = "okay";
	phy-handle = <&qca8075_24>;
	label = "lan1";
  };
  ...
  &dp5 {
    status = "okay";
    phy-handle = <&qca8081>;
    label = "wan";
  };

After:
	switch_lan_bmp = <(ESS_PORT5 | ESS_PORT2 | ESS_PORT3 | ESS_PORT4)>;
	switch_wan_bmp = <ESS_PORT1>;
  ...
  &dp1 {
    status = "okay";
    phy-handle = <&qca8075_24>;
    label = "wan";
  };
  ...
  &dp5 {
    status = "okay";
    phy-handle = <&qca8081>;
    label = "lan1";
  };

DTS Downloads (Before/After)

libwrt DTS files:
Before: ipq6010-re-cs-02.dts
After: ipq6010-re-cs-02.dts

LEDE DTS files:
Before: ipq6010-re-cs-02.dts
After: ipq6010-re-cs-02.dts

VGA Connector Pin Definition

Sun, 18 Jan 2026 00:00:00 +0000

Pin Definition

1. Red video (red wire)
2. Green video (light green wire)
3. Blue video (light blue wire)
4. ID Bit (sometimes RES, or monitor ID2)
5. Self-test (vendor-specific, often GND, black wire)
6. Red ground (4,6,7,8,11 are often tied together as shield)
7. Green ground
8. Blue ground
9. Reserved (vendor-specific, yellow wire)
10. Digital ground (red wire)
11. ID0 (monitor ID bit 0)
12. ID1 (monitor ID bit 1, green wire)
13. Horizontal sync (white wire)
14. Vertical sync (brown wire)
15. ID3 (or monitor ID bit 3, orange wire)

When making a cable:

Connect separately:
  1. Red video
  2. Green video
  3. Blue video
  10. Digital ground
  13. Horizontal sync
  14. Vertical sync

Tie together as shield:
  4. ID Bit (or RES/ID2 depending on vendor)
  6. Red ground
  7. Green ground
  8. Blue ground
  11. ID0

Other wires may be left unconnected.

Winbond Flash Chip Naming Rules Explained (with Full Winbond Flash Part List)

Thu, 01 Jan 2026 00:00:00 +0000

The rules below are only a partial summary. Some part numbers may not follow them exactly. Please always confirm with the specific model list at the end of this article.

Naming Summary

Model Prefix

Winbond flash chip part numbers usually start with W25, such as W25Q64 and W25Q128. W stands for Winbond, and 25 indicates the SPI NOR Flash family. This prefix helps you quickly identify the chip category.

Flash Type and Performance

The letter after W25 indicates flash type/performance:

Letter	Meaning
Q	SPI/Dual/Quad Quad SPI Flash (高性能，支持4线模式)
X	SPI/Dual Standard/Dual SPI Flash (标准或双线模式，通常较老或低成本)
H	SPI/Dual/Quad High Performance (通常也是 Quad SPI，但频率更高或制程不同)
M	SPI/Dual/Quad Stacked Memory (多芯片堆叠，即您提到的 Multiple I/O 或大容量堆叠)
N	SPI/Dual/Quad Serial NAND (在您的文件中，W25N 也支持 SPI/Dual/Quad，但通常指 NAND 架构)

Capacity

The following digits, such as 64 in Q64 and 128 in Q128, represent capacity. For most Mb-class products (16Mb and above), the number directly equals capacity (e.g., 64 = 64Mb, 128 = 128Mb). For small-capacity Mb products (<16Mb), the number is typically divided by 10 (or trailing zero removed), e.g., 80 = 8Mb, 40 = 4Mb. For Gb-class products, 01 means 1Gb and 02 means 2Gb.

Code	Capacity	Example
01	1Gb	W25H01…, W25M02… (堆叠芯片)
02	2Gb	W25M02…
512	512,Mb*	W25M512… (注：部分大容量Mb也会归类在此系列)
05 或	512	512,Mb,W25Q512…
256	256Mb	W25Q256…
128	128Mb	W25Q128…
64	64Mb	“W25Q64…, W25X64…”
32	32Mb	“W25Q32…, W25X32…”
16	16Mb	“W25Q16…, W25X16…”
80	8Mb	“W25Q80…, W25X80… (注: 80 代表 8M)”
40	4Mb	W25X40… (注: 40 代表 4M)
20	2Mb	W25X20… (注: 20 代表 2M)
10	1Mb	W25X10… (注: 10 代表 1M)

Speed Grade

Different flash chips have different read/write performance. Winbond distinguishes them by adding a speed grade suffix to the part number. Common grades are: V: 80MHz clock class, up to 104MHz (lower speed class). F: 100MHz clock class, up to 133MHz (mid speed). J: 120MHz clock class, up to 200MHz (high speed).

Example: W25Q64FV means 64Mbit, Quad-SPI, and 100MHz class.

Package Type and Pin Count

SSIG: 8-pin SOIC wide body; USIG: 8-pin SOIC narrow body; TR: 16-pin TSOP; ZP: 8-pin WSON. These codes are appended at the end of the part number. For example, W25Q64FVSSIG means 64Mbit, Quad-SPI, 100MHz class, in 8-pin SOIC wide body package.

Temperature Range

Finally, Winbond part numbers may include a temperature-range code: 0: operating temperature 0°C to +70°C; I: operating temperature -40°C to +85°C; H: operating temperature -40°C to +105°C. Example: W25Q64FVIH means 64Mbit, Quad-SPI, 100MHz class, with -40°C to +85°C operating range.

Part Number Data List

Part No.	Density	Density unit	STR Frequency (MHz)	DTR Frequency (MHz)	Voltage (min) (V)	Voltage (max) (V)	Temp. (min) (⁰C)	Temp. (max) (⁰C)	Package Type	PIN	Dimension	Dimension unit	Interface Type	Status-Industrial	Status-Automotive	Automotive Grade	On-Chip ECC (bit)	Additional Spec Information
W25H01JVSFAM	1.0	Gb	133	80	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H01JVSFAMG	1.0	Gb	133	80	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H01JVSFSM	1.0	Gb	133	80	2.7	3.6	-40.0	125.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25H01JVSFSMG	1.0	Gb	133	80	2.7	3.6	-40.0	125.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25H01JVTBAM	1.0	Gb	133	80	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H01JVTBAMG	1.0	Gb	133	80	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H01JVTBSM	1.0	Gb	133	80	2.7	3.6	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H01JVTBSMG	1.0	Gb	133	80	2.7	3.6	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H01JVZEAM	1.0	Gb	133	80	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H01JVZEAMG	1.0	Gb	133	80	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H01JVZESM	1.0	Gb	133	80	2.7	3.6	-40.0	125.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H01JVZESMG	1.0	Gb	133	80	2.7	3.6	-40.0	125.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H01NWSFAM	1.0	Gb	133	84	1.7	1.95	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25H01NWSFAMG	1.0	Gb	133	84	1.7	1.95	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25H01NWSFSM	1.0	Gb	133	84	1.7	1.95	-40.0	125.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25H01NWSFSMG	1.0	Gb	133	84	1.7	1.95	-40.0	125.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25H01NWTBAM	1.0	Gb	133	84	1.7	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25H01NWTBAMG	1.0	Gb	133	84	1.7	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25H01NWTBSM	1.0	Gb	133	84	1.7	1.95	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25H01NWTBSMG	1.0	Gb	133	84	1.7	1.95	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25H01NWZEAM	1.0	Gb	133	84	1.7	1.95	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25H01NWZEAMG	1.0	Gb	133	84	1.7	1.95	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25H01NWZESM	1.0	Gb	133	84	1.7	1.95	-40.0	125.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25H01NWZESMG	1.0	Gb	133	84	1.7	1.95	-40.0	125.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25H02JVTBAM	2.0	Gb	133	80	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H02JVTBAMG	2.0	Gb	133	80	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H02JVTBSM	2.0	Gb	133	80	2.7	3.6	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H02JVTBSMG	2.0	Gb	133	80	2.7	3.6	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H02NWTBAM	2.0	Gb	133	84	1.7	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	UD	Yes	1bit	-
W25H02NWTBAMG	2.0	Gb	133	84	1.7	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	UD	Yes	1bit	-
W25H02NWTBSM	2.0	Gb	133	84	1.7	1.95	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	UD	Yes	1bit	-
W25H02NWTBSMG	2.0	Gb	133	84	1.7	1.95	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	UD	Yes	1bit	-
W25H256JVBAM	256.0	Mb	104	80	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H256JVBAMG	256.0	Mb	104	80	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H256JVBSM	256.0	Mb	104	80	2.7	3.6	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H256JVBSMG	256.0	Mb	104	80	2.7	3.6	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H256JVEAM	256.0	Mb	104	80	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H256JVEAMG	256.0	Mb	104	80	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H256JVESM	256.0	Mb	104	80	2.7	3.6	-40.0	125.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H256JVESMG	256.0	Mb	104	80	2.7	3.6	-40.0	125.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H256JVFAM	256.0	Mb	104	80	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H256JVFAMG	256.0	Mb	104	80	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H256JVFSM	256.0	Mb	104	80	2.7	3.6	-40.0	125.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H256JVFSMG	256.0	Mb	104	80	2.7	3.6	-40.0	125.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H512JVBAM	512.0	Mb	133	80	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H512JVBAMG	512.0	Mb	133	80	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H512JVBSM	512.0	Mb	133	80	2.7	3.6	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H512JVBSMG	512.0	Mb	133	80	2.7	3.6	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H512JVEAM	512.0	Mb	133	80	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H512JVEAMG	512.0	Mb	133	80	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H512JVESM	512.0	Mb	133	80	2.7	3.6	-40.0	125.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H512JVESMG	512.0	Mb	133	80	2.7	3.6	-40.0	125.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H512JVFAM	512.0	Mb	133	80	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H512JVFAMG	512.0	Mb	133	80	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H512JVFSM	512.0	Mb	133	80	2.7	3.6	-40.0	115.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H512JVFSMG	512.0	Mb	133	80	2.7	3.6	-40.0	115.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H512NWBAM	512.0	Mb	133	84	1.7	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H512NWBAMG	512.0	Mb	133	84	1.7	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H512NWBSM	512.0	Mb	133	84	1.7	1.95	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H512NWBSMG	512.0	Mb	133	84	1.7	1.95	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H512NWEAM	512.0	Mb	133	84	1.7	1.95	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H512NWEAMG	512.0	Mb	133	84	1.7	1.95	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H512NWESM	512.0	Mb	133	84	1.7	1.95	-40.0	125.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H512NWESMG	512.0	Mb	133	84	1.7	1.95	-40.0	125.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H512NWFAM	512.0	Mb	133	84	1.7	1.95	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H512NWFAMG	512.0	Mb	133	84	1.7	1.95	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H512NWFSM	512.0	Mb	133	84	1.7	1.95	-40.0	125.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes	1bit	-
W25H512NWFSMG	512.0	Mb	133	84	1.7	1.95	-40.0	125.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes	1bit	-
W25M512JVBAM	512.0	Mb	104	52	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25M512JVBAMG	512.0	Mb	104	52	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25M512JVBAQ	512.0	Mb	104	-	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25M512JVBAQG	512.0	Mb	104	-	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25M512JVBSM	512.0	Mb	104	52	2.7	3.6	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25M512JVBSMG	512.0	Mb	104	52	2.7	3.6	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25M512JVBSQ	512.0	Mb	104	-	2.7	3.6	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25M512JVBSQG	512.0	Mb	104	-	2.7	3.6	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25M512JVEAM	512.0	Mb	104	52	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25M512JVEAMG	512.0	Mb	104	52	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25M512JVEAQ	512.0	Mb	104	-	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25M512JVEAQG	512.0	Mb	104	-	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25M512JVESM	512.0	Mb	104	52	2.7	3.6	-40.0	125.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25M512JVESMG	512.0	Mb	104	52	2.7	3.6	-40.0	125.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25M512JVESQ	512.0	Mb	104	-	2.7	3.6	-40.0	125.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25M512JVESQG	512.0	Mb	104	-	2.7	3.6	-40.0	125.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25M512JVFAM	512.0	Mb	104	52	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25M512JVFAMG	512.0	Mb	104	52	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25M512JVFAQ	512.0	Mb	104	-	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25M512JVFAQG	512.0	Mb	104	-	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25M512JVFSM	512.0	Mb	104	52	2.7	3.6	-40.0	125.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25M512JVFSMG	512.0	Mb	104	52	2.7	3.6	-40.0	125.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25M512JVFSQ	512.0	Mb	104	-	2.7	3.6	-40.0	125.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25M512JVFSQG	512.0	Mb	104	-	2.7	3.6	-40.0	125.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25M512JWBAM	512.0	Mb	104	-	1.7	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25M512JWBAMG	512.0	Mb	104	-	1.7	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25M512JWBIQ	512.0	Mb	104	-	1.7	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25M512JWBIQG	512.0	Mb	104	-	1.7	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25M512JWBSQ	512.0	Mb	104	-	1.7	1.95	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25M512JWBSQG	512.0	Mb	104	-	1.7	1.95	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25M512JWEAQ	512.0	Mb	104	-	1.7	1.95	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25M512JWEAQG	512.0	Mb	104	-	1.7	1.95	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25M512JWEIQ	512.0	Mb	104	-	1.7	1.95	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25M512JWEIQG	512.0	Mb	104	-	1.7	1.95	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25M512JWFIQ	512.0	Mb	104	-	1.7	1.95	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25M512JWFIQG	512.0	Mb	104	-	1.7	1.95	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q01JVSFIM	1.0	Gb	133	66	2.7	3.6	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q01JVSFIMG	1.0	Gb	133	66	2.7	3.6	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q01JVSFIQ	1.0	Gb	133	-	2.7	3.6	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q01JVSFIQG	1.0	Gb	133	-	2.7	3.6	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q01JVSFJQ	1.0	Gb	133	-	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q01JVSFJQG	1.0	Gb	133	-	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q01JVTBIM	1.0	Gb	133	66	2.7	3.6	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q01JVTBIMG	1.0	Gb	133	66	2.7	3.6	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q01JVTBIQ	1.0	Gb	133	-	2.7	3.6	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q01JVTBIQG	1.0	Gb	133	-	2.7	3.6	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q01JVTBJQ	1.0	Gb	133	-	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q01JVTBJQG	1.0	Gb	133	-	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q01JVZEIM	1.0	Gb	133	66	2.7	3.6	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q01JVZEIMG	1.0	Gb	133	66	2.7	3.6	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q01JVZEIQ	1.0	Gb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q01JVZEIQG	1.0	Gb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q01JVZEJQ	1.0	Gb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q01JVZEJQG	1.0	Gb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q01NWSFIA	1.0	Gb	133	-	1.7	1.95	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q01NWSFIAG	1.0	Gb	133	-	1.7	1.95	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q01NWSFIM	1.0	Gb	133	84	1.7	1.95	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q01NWSFIMG	1.0	Gb	133	84	1.7	1.95	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q01NWSFIQ	1.0	Gb	133	-	1.7	1.95	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q01NWSFIQG	1.0	Gb	133	-	1.7	1.95	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q01NWSFJM	1.0	Gb	133	84	1.7	1.95	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q01NWSFJMG	1.0	Gb	133	84	1.7	1.95	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q01NWSFJQ	1.0	Gb	133	-	1.7	1.95	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q01NWSFJQG	1.0	Gb	133	-	1.7	1.95	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q01NWTBIA	1.0	Gb	133	-	1.7	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q01NWTBIAG	1.0	Gb	133	-	1.7	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q01NWTBIM	1.0	Gb	133	84	1.7	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q01NWTBIMG	1.0	Gb	133	84	1.7	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q01NWTBIQ	1.0	Gb	133	-	1.7	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q01NWTBIQG	1.0	Gb	133	-	1.7	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q01NWTBJM	1.0	Gb	133	84	1.7	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q01NWTBJMG	1.0	Gb	133	84	1.7	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q01NWTBJQ	1.0	Gb	133	-	1.7	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q01NWTBJQG	1.0	Gb	133	-	1.7	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q01NWZEIM	1.0	Gb	133	84	1.7	1.95	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q01NWZEIMG	1.0	Gb	133	84	1.7	1.95	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q01NWZEIQ	1.0	Gb	133	-	1.7	1.95	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q01NWZEIQG	1.0	Gb	133	-	1.7	1.95	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q01NWZEJM	1.0	Gb	133	84	1.7	1.95	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q01NWZEJMG	1.0	Gb	133	84	1.7	1.95	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q01NWZEJQ	1.0	Gb	133	-	1.7	1.95	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q01NWZEJQG	1.0	Gb	133	-	1.7	1.95	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q01RVSFJM	1.0	Gb	133	104	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No	1bit	-
W25Q01RVSFJMG	1.0	Gb	133	104	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No	1bit	-
W25Q01RVSFJQ	1.0	Gb	133	-	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No	1bit	-
W25Q01RVSFJQG	1.0	Gb	133	-	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No	1bit	-
W25Q01RVTBJM	1.0	Gb	133	104	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No	1bit	-
W25Q01RVTBJMG	1.0	Gb	133	104	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No	1bit	-
W25Q01RVTBJQ	1.0	Gb	133	-	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No	1bit	-
W25Q01RVTBJQG	1.0	Gb	133	-	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No	1bit	-
W25Q01RVZEJM	1.0	Gb	133	104	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No	1bit	-
W25Q01RVZEJMG	1.0	Gb	133	104	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No	1bit	-
W25Q01RVZEJQ	1.0	Gb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No	1bit	-
W25Q01RVZEJQG	1.0	Gb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No	1bit	-
W25Q02JVTBIM	2.0	Gb	133	66	2.7	3.6	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q02JVTBIMG	2.0	Gb	133	66	2.7	3.6	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q02NWTBIA	2.0	Gb	133	84	1.7	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q02NWTBIAG	2.0	Gb	133	84	1.7	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q02NWTBIM	2.0	Gb	133	84	1.7	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q02NWTBIMG	2.0	Gb	133	84	1.7	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q02RVSFJM	2.0	Gb	133	104	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No	1bit	-
W25Q02RVSFJMG	2.0	Gb	133	104	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No	1bit	-
W25Q02RVSFJQ	2.0	Gb	133	-	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No	1bit	-
W25Q02RVSFJQG	2.0	Gb	133	-	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No	1bit	-
W25Q02RVTBJM	2.0	Gb	133	104	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No	1bit	-
W25Q02RVTBJMG	2.0	Gb	133	104	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No	1bit	-
W25Q02RVTBJQ	2.0	Gb	133	-	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No	1bit	-
W25Q02RVTBJQG	2.0	Gb	133	-	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No	1bit	-
W25Q02RVZEJM	2.0	Gb	133	104	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No	1bit	-
W25Q02RVZEJMG	2.0	Gb	133	104	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No	1bit	-
W25Q02RVZEJQ	2.0	Gb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No	1bit	-
W25Q02RVZEJQG	2.0	Gb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No	1bit	-
W25Q10EWBYIG	1.0	Mb	104	-	1.65	1.95	-40.0	85.0	WLCSP	8.0			SPI/Dual/Quad	P	-	No		-
W25Q10EWBYIGG	1.0	Mb	104	-	1.65	1.95	-40.0	85.0	WLCSP	8.0			SPI/Dual/Quad	P	-	No		-
W25Q10EWUXIE	1.0	Mb	104	-	1.65	1.95	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q10EWUXIEG	1.0	Mb	104	-	1.65	1.95	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q10RLSNJM	1.0	Mb	133	84	2.3	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q10RLSNJMG	1.0	Mb	133	84	2.3	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q10RLSNJQ	1.0	Mb	133	-	2.3	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q10RLSNJQG	1.0	Mb	133	-	2.3	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q10RLXHJM	1.0	Mb	133	84	2.3	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q10RLXHJMG	1.0	Mb	133	84	2.3	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q10RLXHJQ	1.0	Mb	133	-	2.3	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q10RLXHJQG	1.0	Mb	133	-	2.3	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JVBAM	128.0	Mb	133	66	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVBAMG	128.0	Mb	133	66	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVBAQ	128.0	Mb	133	-	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVBAQG	128.0	Mb	133	-	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVBIM	128.0	Mb	133	66	2.7	3.6	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JVBIMG	128.0	Mb	133	66	2.7	3.6	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JVBIQ	128.0	Mb	133	-	2.7	3.6	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JVBIQG	128.0	Mb	133	-	2.7	3.6	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JVBJM	128.0	Mb	133	66	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JVBJMG	128.0	Mb	133	66	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JVBJQ	128.0	Mb	133	-	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JVBJQG	128.0	Mb	133	-	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JVBSM	128.0	Mb	133	66	2.7	3.6	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVBSMG	128.0	Mb	133	66	2.7	3.6	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVBSQ	128.0	Mb	133	-	2.7	3.6	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVBSQG	128.0	Mb	133	-	2.7	3.6	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVCAQ	128.0	Mb	133	-	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVCAQG	128.0	Mb	133	-	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVCIM	128.0	Mb	133	66	2.7	3.6	-40.0	85.0	TFBGA (4X6)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JVCIMG	128.0	Mb	133	66	2.7	3.6	-40.0	85.0	TFBGA (4X6)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JVCIQ	128.0	Mb	133	-	2.7	3.6	-40.0	85.0	TFBGA (4X6)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JVCIQG	128.0	Mb	133	-	2.7	3.6	-40.0	85.0	TFBGA (4X6)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JVCJQ	128.0	Mb	133	-	2.7	3.6	-40.0	105.0	TFBGA (4X6)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JVCJQG	128.0	Mb	133	-	2.7	3.6	-40.0	105.0	TFBGA (4X6)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JVCSQ	128.0	Mb	133	-	2.7	3.6	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVCSQG	128.0	Mb	133	-	2.7	3.6	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVEAM	128.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVEAMG	128.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVEAQ	128.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVEAQG	128.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVEIM	128.0	Mb	133	66	2.7	3.6	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JVEIMG	128.0	Mb	133	66	2.7	3.6	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JVEIN	128.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		DRV=75%
W25Q128JVEING	128.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		DRV=75%
W25Q128JVEIQ	128.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JVEIQG	128.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JVEJM	128.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JVEJMG	128.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JVEJQ	128.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JVEJQG	128.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JVESM	128.0	Mb	133	66	2.7	3.6	-40.0	125.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVESMG	128.0	Mb	133	66	2.7	3.6	-40.0	125.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVESQ	128.0	Mb	133	-	2.7	3.6	-40.0	125.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVESQG	128.0	Mb	133	-	2.7	3.6	-40.0	125.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVFAM	128.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVFAMG	128.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVFAQ	128.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVFAQG	128.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVFIM	128.0	Mb	133	66	2.7	3.6	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q128JVFIMG	128.0	Mb	133	66	2.7	3.6	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q128JVFIQ	128.0	Mb	133	-	2.7	3.6	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q128JVFIQG	128.0	Mb	133	-	2.7	3.6	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q128JVFJM	128.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q128JVFJMG	128.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q128JVFJQ	128.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q128JVFJQG	128.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q128JVFSM	128.0	Mb	133	66	2.7	3.6	-40.0	125.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVFSMG	128.0	Mb	133	66	2.7	3.6	-40.0	125.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVFSQ	128.0	Mb	133	-	2.7	3.6	-40.0	125.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVFSQG	128.0	Mb	133	-	2.7	3.6	-40.0	125.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVPAM	128.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVPAMG	128.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVPAQ	128.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVPAQG	128.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVPIM	128.0	Mb	133	66	2.7	3.6	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JVPIMG	128.0	Mb	133	66	2.7	3.6	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JVPIN	128.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		DRV=75%
W25Q128JVPING	128.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		DRV=75%
W25Q128JVPIQ	128.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JVPIQG	128.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JVPJM	128.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JVPJMG	128.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JVPJQ	128.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JVPJQG	128.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JVPSM	128.0	Mb	133	66	2.7	3.6	-40.0	125.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVPSMG	128.0	Mb	133	66	2.7	3.6	-40.0	125.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVPSQ	128.0	Mb	133	-	2.7	3.6	-40.0	125.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVPSQG	128.0	Mb	133	-	2.7	3.6	-40.0	125.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVSAM	128.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVSAMG	128.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVSAQ	128.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVSAQG	128.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVSIM	128.0	Mb	133	66	2.7	3.6	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q128JVSIMG	128.0	Mb	133	66	2.7	3.6	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q128JVSIN	128.0	Mb	133	-	2.7	3.6	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		DRV=75%
W25Q128JVSING	128.0	Mb	133	-	2.7	3.6	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		DRV=75%
W25Q128JVSIQ	128.0	Mb	133	-	2.7	3.6	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q128JVSIQG	128.0	Mb	133	-	2.7	3.6	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q128JVSJM	128.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q128JVSJMG	128.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q128JVSJQ	128.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q128JVSJQG	128.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q128JVSSM	128.0	Mb	133	66	2.7	3.6	-40.0	125.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVSSMG	128.0	Mb	133	66	2.7	3.6	-40.0	125.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVSSQ	128.0	Mb	133	-	2.7	3.6	-40.0	125.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVSSQG	128.0	Mb	133	-	2.7	3.6	-40.0	125.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q128JVYIQ	128.0	Mb	133	-	2.7	3.6	-40.0	85.0	WLCSP	24.0			SPI/Dual/Quad	P	-	No		-
W25Q128JVYIQG	128.0	Mb	133	-	2.7	3.6	-40.0	85.0	WLCSP	24.0			SPI/Dual/Quad	P	-	No		-
W25Q128JWBAM	128.0	Mb	104	52	1.7	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JWBAMG	128.0	Mb	104	52	1.7	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JWBAQ	128.0	Mb	104	-	1.7	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JWBAQG	128.0	Mb	104	-	1.7	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JWBIM	128.0	Mb	133	66	1.7	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JWBIMG	128.0	Mb	133	66	1.7	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JWBIQ	128.0	Mb	133	-	1.7	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JWBIQG	128.0	Mb	133	-	1.7	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JWBJQ	128.0	Mb	133	-	1.7	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JWBJQG	128.0	Mb	133	-	1.7	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JWBSM	128.0	Mb	104	52	1.7	1.95	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JWBSMG	128.0	Mb	104	52	1.7	1.95	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JWBSQ	128.0	Mb	104	-	1.7	1.95	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JWBSQG	128.0	Mb	104	-	1.7	1.95	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JWEIM	128.0	Mb	133	66	1.7	1.95	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JWEIMG	128.0	Mb	133	66	1.7	1.95	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JWEIN	128.0	Mb	133	-	1.7	1.95	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		DRV=75%
W25Q128JWEING	128.0	Mb	133	-	1.7	1.95	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		DRV=75%
W25Q128JWEIQ	128.0	Mb	133	-	1.7	1.95	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JWEIQG	128.0	Mb	133	-	1.7	1.95	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JWEJQ	128.0	Mb	133	-	1.7	1.95	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JWEJQG	128.0	Mb	133	-	1.7	1.95	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JWFAM	128.0	Mb	104	52	1.7	1.95	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q128JWFAMG	128.0	Mb	104	52	1.7	1.95	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q128JWFAQ	128.0	Mb	104	-	1.7	1.95	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q128JWFAQG	128.0	Mb	104	-	1.7	1.95	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q128JWFIM	128.0	Mb	133	66	1.7	1.95	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q128JWFIMG	128.0	Mb	133	66	1.7	1.95	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q128JWFIN	128.0	Mb	133	-	1.7	1.95	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		DRV=75%
W25Q128JWFING	128.0	Mb	133	-	1.7	1.95	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		DRV=75%
W25Q128JWFIQ	128.0	Mb	133	-	1.7	1.95	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q128JWFIQG	128.0	Mb	133	-	1.7	1.95	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q128JWFSM	128.0	Mb	104	52	1.7	1.95	-40.0	125.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q128JWFSMG	128.0	Mb	104	52	1.7	1.95	-40.0	125.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q128JWPAM	128.0	Mb	104	52	1.7	1.95	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JWPAMG	128.0	Mb	104	52	1.7	1.95	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JWPAQ	128.0	Mb	104	-	1.7	1.95	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JWPAQG	128.0	Mb	104	-	1.7	1.95	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JWPIM	128.0	Mb	133	66	1.7	1.95	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JWPIMG	128.0	Mb	133	66	1.7	1.95	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JWPIQ	128.0	Mb	133	-	1.7	1.95	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JWPIQG	128.0	Mb	133	-	1.7	1.95	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JWPJM	128.0	Mb	133	66	1.7	1.95	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JWPJMG	128.0	Mb	133	66	1.7	1.95	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JWPJQ	128.0	Mb	133	-	1.7	1.95	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JWPJQG	128.0	Mb	133	-	1.7	1.95	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q128JWPSM	128.0	Mb	104	52	1.7	1.95	-40.0	125.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JWPSMG	128.0	Mb	104	52	1.7	1.95	-40.0	125.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JWPSQ	128.0	Mb	104	-	1.7	1.95	-40.0	125.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JWPSQG	128.0	Mb	104	-	1.7	1.95	-40.0	125.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q128JWSAQ	128.0	Mb	104	-	1.7	1.95	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q128JWSAQG	128.0	Mb	104	-	1.7	1.95	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q128JWSIM	128.0	Mb	133	66	1.7	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q128JWSIMG	128.0	Mb	133	66	1.7	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q128JWSIN	128.0	Mb	133	-	1.7	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		DRV=75%
W25Q128JWSING	128.0	Mb	133	-	1.7	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		DRV=75%
W25Q128JWSIQ	128.0	Mb	133	-	1.7	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q128JWSIQG	128.0	Mb	133	-	1.7	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q128JWSJQ	128.0	Mb	133	-	1.7	1.95	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q128JWSJQG	128.0	Mb	133	-	1.7	1.95	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q128JWSSQ	128.0	Mb	104	-	1.7	1.95	-40.0	125.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q128JWSSQG	128.0	Mb	104	-	1.7	1.95	-40.0	125.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q128JWYIM	128.0	Mb	133	66	1.7	1.95	-40.0	85.0	WLCSP	21.0			SPI/Dual/Quad	P	-	No		-
W25Q128JWYIMG	128.0	Mb	133	66	1.7	1.95	-40.0	85.0	WLCSP	21.0			SPI/Dual/Quad	P	-	No		-
W25Q128JWYIQ	128.0	Mb	133	-	1.7	1.95	-40.0	85.0	WLCSP	21.0			SPI/Dual/Quad	P	-	No		-
W25Q128JWYIQG	128.0	Mb	133	-	1.7	1.95	-40.0	85.0	WLCSP	21.0			SPI/Dual/Quad	P	-	No		-
W25Q128JWYJQ	128.0	Mb	133	-	1.7	1.95	-40.0	105.0	WLCSP	21.0			SPI/Dual/Quad	P	-	No		-
W25Q128JWYJQG	128.0	Mb	133	-	1.7	1.95	-40.0	105.0	WLCSP	21.0			SPI/Dual/Quad	P	-	No		-
W25Q12PWBYIH	128.0	Mb	166	104	1.65	1.95	-40.0	85.0	WLCSP	16.0			SPI/Dual/Quad	P	-	No		-
W25Q12PWBYIHG	128.0	Mb	166	104	1.65	1.95	-40.0	85.0	WLCSP	16.0			SPI/Dual/Quad	P	-	No		-
W25Q12PWBYIM	128.0	Mb	166	104	1.65	1.95	-40.0	85.0	WLCSP	16.0			SPI/Dual/Quad	P	-	No		-
W25Q12PWBYIMG	128.0	Mb	166	104	1.65	1.95	-40.0	85.0	WLCSP	16.0			SPI/Dual/Quad	P	-	No		-
W25Q12PWSFIM	128.0	Mb	166	104	1.65	1.95	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q12PWSFIMG	128.0	Mb	166	104	1.65	1.95	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q12PWSFIQ	128.0	Mb	166	104	1.65	1.95	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q12PWSFIQG	128.0	Mb	166	104	1.65	1.95	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q12PWSSIM	128.0	Mb	166	104	1.65	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q12PWSSIMG	128.0	Mb	166	104	1.65	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q12PWSSIQ	128.0	Mb	166	104	1.65	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q12PWSSIQG	128.0	Mb	166	104	1.65	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q12PWTBIQ	128.0	Mb	166	104	1.65	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q12PWTBIQG	128.0	Mb	166	104	1.65	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q12PWUUIQ	128.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q12PWUUIQG	128.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q12PWXGIQ	128.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q12PWXGIQG	128.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q12PWZEIM	128.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q12PWZEIMG	128.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q12PWZEIQ	128.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q12PWZEIQG	128.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q12PWZPIM	128.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q12PWZPIMG	128.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q12PWZPIQ	128.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q12PWZPIQG	128.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q12RVCFJM	128.0	Mb	133	104	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	UD	-	No		-
W25Q12RVCFJMG	128.0	Mb	133	104	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	UD	-	No		-
W25Q12RVCFJQ	128.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	UD	-	No		-
W25Q12RVCFJQG	128.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	UD	-	No		-
W25Q12RVCJJM			133	104	2.7	3.6							SPI/Dual/Quad	UD	-	No		-
W25Q12RVCJJMG			133	104	2.7	3.6							SPI/Dual/Quad	UD	-	No		-
W25Q12RVCJJQ			133	-	2.7	3.6							SPI/Dual/Quad	UD	-	No		-
W25Q12RVCJJQG			133	-	2.7	3.6							SPI/Dual/Quad	UD	-	No		-
W25Q12RVCPJM	128.0	Mb	133	104	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	UD	-	No		-
W25Q12RVCPJMG	128.0	Mb	133	104	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	UD	-	No		-
W25Q12RVCPJQ	128.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	UD	-	No		-
W25Q12RVCPJQG	128.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	UD	-	No		-
W25Q12RVCSJM	128.0	Mb	133	104	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	UD	-	No		-
W25Q12RVCSJMG	128.0	Mb	133	104	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	UD	-	No		-
W25Q12RVCSJQ	128.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	UD	-	No		-
W25Q12RVCSJQG	128.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	UD	-	No		-
W25Q16JLSNIG	16.0	Mb	104	-	2.3	3.6	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16JLSNIGG	16.0	Mb	104	-	2.3	3.6	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16JLSSIG	16.0	Mb	104	-	2.3	3.6	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16JLSSIGG	16.0	Mb	104	-	2.3	3.6	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16JLUXIG	16.0	Mb	104	-	2.3	3.6	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JLUXIGG	16.0	Mb	104	-	2.3	3.6	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JLZPIG	16.0	Mb	104	-	2.3	3.6	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JLZPIGG	16.0	Mb	104	-	2.3	3.6	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JVBYIQ	16.0	Mb	133	-	2.7	3.6	-40.0	85.0	WLCSP	8.0			SPI/Dual/Quad	P	-	No		-
W25Q16JVBYIQG	16.0	Mb	133	-	2.7	3.6	-40.0	85.0	WLCSP	8.0			SPI/Dual/Quad	P	-	No		-
W25Q16JVBYJQ	16.0	Mb	133	-	2.7	3.6	-40.0	105.0	WLCSP	8.0			SPI/Dual/Quad	P	-	No		-
W25Q16JVBYJQG	16.0	Mb	133	-	2.7	3.6	-40.0	105.0	WLCSP	8.0			SPI/Dual/Quad	P	-	No		-
W25Q16JVSNAM	16.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVSNAMG	16.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVSNAQ	16.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVSNAQG	16.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVSNIM	16.0	Mb	133	66	2.7	3.6	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16JVSNIMG	16.0	Mb	133	66	2.7	3.6	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16JVSNIQ	16.0	Mb	133	-	2.7	3.6	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16JVSNIQG	16.0	Mb	133	-	2.7	3.6	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16JVSNJM	16.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16JVSNJMG	16.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16JVSNJQ	16.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16JVSNJQG	16.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16JVSNSM	16.0	Mb	133	66	2.7	3.6	-40.0	125.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVSNSMG	16.0	Mb	133	66	2.7	3.6	-40.0	125.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVSNSQ	16.0	Mb	133	-	2.7	3.6	-40.0	125.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVSNSQG	16.0	Mb	133	-	2.7	3.6	-40.0	125.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVSSAM	16.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVSSAMG	16.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVSSAQ	16.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVSSAQG	16.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVSSIM	16.0	Mb	133	66	2.7	3.6	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16JVSSIMG	16.0	Mb	133	66	2.7	3.6	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16JVSSIQ	16.0	Mb	133	-	2.7	3.6	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16JVSSIQG	16.0	Mb	133	-	2.7	3.6	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16JVSSJM	16.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16JVSSJMG	16.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16JVSSJQ	16.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16JVSSJQG	16.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16JVSSSM	16.0	Mb	133	66	2.7	3.6	-40.0	125.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVSSSMG	16.0	Mb	133	66	2.7	3.6	-40.0	125.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVSSSQ	16.0	Mb	133	-	2.7	3.6	-40.0	125.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVSSSQG	16.0	Mb	133	-	2.7	3.6	-40.0	125.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVTBIM	16.0	Mb	133	66	2.7	3.6	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JVTBIMG	16.0	Mb	133	66	2.7	3.6	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JVUUAM	16.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVUUAMG	16.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVUUAQ	16.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVUUAQG	16.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVUUIM	16.0	Mb	133	66	2.7	3.6	-40.0	85.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JVUUIMG	16.0	Mb	133	66	2.7	3.6	-40.0	85.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JVUUIQ	16.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JVUUIQG	16.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JVUUJM	16.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JVUUJMG	16.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JVUUJQ	16.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JVUUJQG	16.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JVUUSM	16.0	Mb	133	66	2.7	3.6	-40.0	125.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVUUSMG	16.0	Mb	133	66	2.7	3.6	-40.0	125.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVUUSQ	16.0	Mb	133	-	2.7	3.6	-40.0	125.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVUUSQG	16.0	Mb	133	-	2.7	3.6	-40.0	125.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVUXAM	16.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVUXAMG	16.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVUXAQ	16.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVUXAQG	16.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVUXIM	16.0	Mb	133	66	2.7	3.6	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JVUXIMG	16.0	Mb	133	66	2.7	3.6	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JVUXIQ	16.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JVUXIQG	16.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JVUXJM	16.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JVUXJMG	16.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JVUXJQ	16.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JVUXJQG	16.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JVUXSM	16.0	Mb	133	66	2.7	3.6	-40.0	125.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVUXSMG	16.0	Mb	133	66	2.7	3.6	-40.0	125.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVUXSQ	16.0	Mb	133	-	2.7	3.6	-40.0	125.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVUXSQG	16.0	Mb	133	-	2.7	3.6	-40.0	125.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVXGAQ	16.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVXGAQG	16.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVXGIQ	16.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JVXGIQG	16.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JVXGJQ	16.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JVXGJQG	16.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JVXGSQ	16.0	Mb	133	-	2.7	3.6	-40.0	125.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVXGSQG	16.0	Mb	133	-	2.7	3.6	-40.0	125.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVZPAM	16.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVZPAMG	16.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVZPAQ	16.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVZPAQG	16.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVZPIM	16.0	Mb	133	66	2.7	3.6	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JVZPIMG	16.0	Mb	133	66	2.7	3.6	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JVZPIQ	16.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JVZPIQG	16.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JVZPJM	16.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JVZPJMG	16.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JVZPJQ	16.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JVZPJQG	16.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JVZPSM	16.0	Mb	133	66	2.7	3.6	-40.0	125.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVZPSMG	16.0	Mb	133	66	2.7	3.6	-40.0	125.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVZPSQ	16.0	Mb	133	-	2.7	3.6	-40.0	125.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JVZPSQG	16.0	Mb	133	-	2.7	3.6	-40.0	125.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JWBYIM	16.0	Mb	133	66	1.65	1.95	-40.0	85.0	WLCSP	8.0			SPI/Dual/Quad	P	-	No		-
W25Q16JWBYIMG	16.0	Mb	133	66	1.65	1.95	-40.0	85.0	WLCSP	8.0			SPI/Dual/Quad	P	-	No		-
W25Q16JWBYIQ	16.0	Mb	133	-	1.65	1.95	-40.0	85.0	WLCSP	8.0			SPI/Dual/Quad	P	-	No		-
W25Q16JWBYIQG	16.0	Mb	133	-	1.65	1.95	-40.0	85.0	WLCSP	8.0			SPI/Dual/Quad	P	-	No		-
W25Q16JWSNAM	16.0	Mb	104	66	1.7	1.95	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q16JWSNAMG	16.0	Mb	104	66	1.7	1.95	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q16JWSNAQ	16.0	Mb	104	-	1.7	1.95	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q16JWSNAQG	16.0	Mb	104	-	1.7	1.95	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q16JWSNIM	16.0	Mb	133	66	1.65	1.95	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16JWSNIMG	16.0	Mb	133	66	1.65	1.95	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16JWSNIQ	16.0	Mb	133	-	1.65	1.95	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16JWSNIQG	16.0	Mb	133	-	1.65	1.95	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16JWSNJQ	16.0	Mb	133	-	1.65	1.95	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16JWSNJQG	16.0	Mb	133	-	1.65	1.95	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16JWSNSM	16.0	Mb	104	66	1.7	1.95	-40.0	125.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q16JWSNSMG	16.0	Mb	104	66	1.7	1.95	-40.0	125.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q16JWSNSQ	16.0	Mb	104	-	1.7	1.95	-40.0	125.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q16JWSNSQG	16.0	Mb	104	-	1.7	1.95	-40.0	125.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q16JWSSAQ	16.0	Mb	104	-	1.7	1.95	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q16JWSSAQG	16.0	Mb	104	-	1.7	1.95	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q16JWSSIM	16.0	Mb	133	66	1.65	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16JWSSIMG	16.0	Mb	133	66	1.65	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16JWSSIQ	16.0	Mb	133	-	1.65	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16JWSSIQG	16.0	Mb	133	-	1.65	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16JWSSJQ	16.0	Mb	133	-	1.65	1.95	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16JWSSJQG	16.0	Mb	133	-	1.65	1.95	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16JWSSSQ	16.0	Mb	104	-	1.7	1.95	-40.0	125.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q16JWSSSQG	16.0	Mb	104	-	1.7	1.95	-40.0	125.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q16JWUUAQ	16.0	Mb	104	-	1.7	1.95	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JWUUAQG	16.0	Mb	104	-	1.7	1.95	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JWUUIQ	16.0	Mb	133	-	1.65	1.95	-40.0	85.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JWUUIQG	16.0	Mb	133	-	1.65	1.95	-40.0	85.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JWUUJQ	16.0	Mb	133	-	1.65	1.95	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JWUUJQG	16.0	Mb	133	-	1.65	1.95	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JWUUSQ	16.0	Mb	104	-	1.7	1.95	-40.0	125.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JWUUSQG	16.0	Mb	104	-	1.7	1.95	-40.0	125.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JWXHAQ	16.0	Mb	104	-	1.7	1.95	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JWXHAQG	16.0	Mb	104	-	1.7	1.95	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JWXHIM	16.0	Mb	133	66	1.65	1.95	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JWXHIMG	16.0	Mb	133	66	1.65	1.95	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JWXHIQ	16.0	Mb	133	-	1.65	1.95	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JWXHIQG	16.0	Mb	133	-	1.65	1.95	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JWXHJQ	16.0	Mb	133	-	1.65	1.95	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JWXHJQG	16.0	Mb	133	-	1.65	1.95	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JWXHSQ	16.0	Mb	104	-	1.7	1.95	-40.0	125.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JWXHSQG	16.0	Mb	104	-	1.7	1.95	-40.0	125.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JWZPAQ	16.0	Mb	104	-	1.7	1.95	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JWZPAQG	16.0	Mb	104	-	1.7	1.95	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q16JWZPIM	16.0	Mb	133	66	1.65	1.95	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JWZPIMG	16.0	Mb	133	66	1.65	1.95	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JWZPIQ	16.0	Mb	133	-	1.65	1.95	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JWZPIQG	16.0	Mb	133	-	1.65	1.95	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JWZPJQ	16.0	Mb	133	-	1.65	1.95	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16JWZPJQG	16.0	Mb	133	-	1.65	1.95	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16PWSNIM	16.0	Mb	166	104	1.65	1.95	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	S	-	No		-
W25Q16PWSNIMG	16.0	Mb	166	104	1.65	1.95	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	S	-	No		-
W25Q16PWSNIQ	16.0	Mb	166	-	1.65	1.95	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	S	-	No		-
W25Q16PWSNIQG	16.0	Mb	166	-	1.65	1.95	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	S	-	No		-
W25Q16PWSSIM	16.0	Mb	166	104	1.65	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	S	-	No		-
W25Q16PWSSIMG	16.0	Mb	166	104	1.65	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	S	-	No		-
W25Q16PWSSIQ	16.0	Mb	166	-	1.65	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	S	-	No		-
W25Q16PWSSIQG	16.0	Mb	166	-	1.65	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	S	-	No		-
W25Q16PWUUIM	16.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q16PWUUIMG	16.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q16PWUUIQ	16.0	Mb	166	-	1.65	1.95	-40.0	85.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q16PWUUIQG	16.0	Mb	166	-	1.65	1.95	-40.0	85.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q16PWXHIM	16.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q16PWXHIMG	16.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q16PWXHIQ	16.0	Mb	166	-	1.65	1.95	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q16PWXHIQG	16.0	Mb	166	-	1.65	1.95	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q16RVCNJM	16.0	Mb	133	84	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16RVCNJMG	16.0	Mb	133	84	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16RVCNJQ	16.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16RVCNJQG	16.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16RVCPJM	16.0	Mb	133	84	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16RVCPJMG	16.0	Mb	133	84	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16RVCPJQ	16.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16RVCPJQG	16.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16RVCSJM	16.0	Mb	133	84	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16RVCSJMG	16.0	Mb	133	84	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16RVCSJQ	16.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16RVCSJQG	16.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q16RVXHJM	16.0	Mb	133	84	2.7	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16RVXHJMG	16.0	Mb	133	84	2.7	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16RVXHJQ	16.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q16RVXHJQG	16.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q20CLSNIG	2.0	Mb	104	-	2.3	3.6	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q20CLSNIGG	2.0	Mb	104	-	2.3	3.6	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q20CLUXIG	2.0	Mb	104	-	2.3	3.6	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q20CLUXIGG	2.0	Mb	104	-	2.3	3.6	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q20EWBYIG	2.0	Mb	104	-	1.65	1.95	-40.0	85.0	WLCSP	8.0			SPI/Dual/Quad	P	-	No		-
W25Q20EWBYIGG	2.0	Mb	104	-	1.65	1.95	-40.0	85.0	WLCSP	8.0			SPI/Dual/Quad	P	-	No		-
W25Q20EWSNIG	2.0	Mb	104	-	1.65	1.95	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q20EWSNIGG	2.0	Mb	104	-	1.65	1.95	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q20EWSNJG	2.0	Mb	104	-	1.65	1.95	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q20EWSNJGG	2.0	Mb	104	-	1.65	1.95	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q20EWUXIE	2.0	Mb	104	-	1.65	1.95	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q20EWUXIEG	2.0	Mb	104	-	1.65	1.95	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q20RLSNJM	2.0	Mb	133	84	2.3	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q20RLSNJMG	2.0	Mb	133	84	2.3	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q20RLSNJQ	2.0	Mb	133	-	2.3	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q20RLSNJQG	2.0	Mb	133	-	2.3	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q20RLXHJM	2.0	Mb	133	84	2.3	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q20RLXHJMG	2.0	Mb	133	84	2.3	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q20RLXHJQ	2.0	Mb	133	-	2.3	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q20RLXHJQG	2.0	Mb	133	-	2.3	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q21EWSNAG	2.0	Mb	104	-	1.65	1.95	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q21EWSNAGG	2.0	Mb	104	-	1.65	1.95	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q21EWSNSG	2.0	Mb	104	-	1.65	1.95	-40.0	125.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q21EWSNSGG	2.0	Mb	104	-	1.65	1.95	-40.0	125.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q21EWXHAG	2.0	Mb	104	-	1.65	1.95	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q21EWXHAGG	2.0	Mb	104	-	1.65	1.95	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q21EWXHSG	2.0	Mb	104	-	1.65	1.95	-40.0	125.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q21EWXHSGG	2.0	Mb	104	-	1.65	1.95	-40.0	125.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JVBAM	256.0	Mb	133	66	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JVBAMG	256.0	Mb	133	66	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JVBAQ	256.0	Mb	104	-	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JVBAQG	256.0	Mb	104	-	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JVBIM	256.0	Mb	133	66	2.7	3.6	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JVBIMG	256.0	Mb	133	66	2.7	3.6	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JVBIQ	256.0	Mb	133	-	2.7	3.6	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JVBIQG	256.0	Mb	133	-	2.7	3.6	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JVBJM	256.0	Mb	133	66	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JVBJMG	256.0	Mb	133	66	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JVBJQ	256.0	Mb	133	-	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JVBJQG	256.0	Mb	133	-	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JVBSM	256.0	Mb	133	66	2.7	3.6	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JVBSMG	256.0	Mb	133	66	2.7	3.6	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JVBSQ	256.0	Mb	104	-	2.7	3.6	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JVBSQG	256.0	Mb	104	-	2.7	3.6	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JVCAQ	256.0	Mb	104	-	2.7	3.6	-40.0	85.0	TFBGA (4X6)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JVCAQG	256.0	Mb	104	-	2.7	3.6	-40.0	85.0	TFBGA (4X6)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JVCIM	256.0	Mb	133	66	2.7	3.6	-40.0	85.0	TFBGA (4X6)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JVCIMG	256.0	Mb	133	66	2.7	3.6	-40.0	85.0	TFBGA (4X6)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JVCIQ	256.0	Mb	133	-	2.7	3.6	-40.0	85.0	TFBGA (4X6)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JVCIQG	256.0	Mb	133	-	2.7	3.6	-40.0	85.0	TFBGA (4X6)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JVCJQ	256.0	Mb	133	-	2.7	3.6	-40.0	105.0	TFBGA (4X6)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JVCJQG	256.0	Mb	133	-	2.7	3.6	-40.0	105.0	TFBGA (4X6)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JVEAM	256.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JVEAMG	256.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JVEAQ	256.0	Mb	104	-	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JVEAQG	256.0	Mb	104	-	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JVEIM	256.0	Mb	133	66	2.7	3.6	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JVEIMG	256.0	Mb	133	66	2.7	3.6	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JVEIN	256.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		DRV=75%
W25Q256JVEING	256.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		DRV=75%
W25Q256JVEIQ	256.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JVEIQG	256.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JVEJM	256.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JVEJMG	256.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JVEJQ	256.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JVEJQG	256.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JVESM	256.0	Mb	133	66	2.7	3.6	-40.0	125.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JVESMG	256.0	Mb	133	66	2.7	3.6	-40.0	125.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JVESQ	256.0	Mb	104	-	2.7	3.6	-40.0	125.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JVESQG	256.0	Mb	104	-	2.7	3.6	-40.0	125.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JVFAM	256.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q256JVFAMG	256.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q256JVFAQ	256.0	Mb	104	-	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q256JVFAQG	256.0	Mb	104	-	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q256JVFIM	256.0	Mb	133	66	2.7	3.6	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q256JVFIMG	256.0	Mb	133	66	2.7	3.6	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q256JVFIN	256.0	Mb	133	-	2.7	3.6	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		DRV=75%
W25Q256JVFING	256.0	Mb	133	-	2.7	3.6	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		DRV=75%
W25Q256JVFIQ	256.0	Mb	133	-	2.7	3.6	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q256JVFIQG	256.0	Mb	133	-	2.7	3.6	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q256JVFJM	256.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q256JVFJMG	256.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q256JVFJQ	256.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q256JVFJQG	256.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q256JVFSM	256.0	Mb	133	66	2.7	3.6	-40.0	125.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q256JVFSMG	256.0	Mb	133	66	2.7	3.6	-40.0	125.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q256JVFSQ	256.0	Mb	104	-	2.7	3.6	-40.0	125.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q256JVFSQG	256.0	Mb	104	-	2.7	3.6	-40.0	125.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q256JWBAM	256.0	Mb	104	66	1.7	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JWBAMG	256.0	Mb	104	66	1.7	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JWBAQ	256.0	Mb	104	-	1.7	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JWBAQG	256.0	Mb	104	-	1.7	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JWBIM	256.0	Mb	133	66	1.7	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JWBIMG	256.0	Mb	133	66	1.7	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JWBIQ	256.0	Mb	133	-	1.7	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JWBIQG	256.0	Mb	133	-	1.7	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JWBSM	256.0	Mb	104	66	1.7	1.95	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JWBSMG	256.0	Mb	104	66	1.7	1.95	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JWBSQ	256.0	Mb	104	-	1.7	1.95	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JWBSQG	256.0	Mb	104	-	1.7	1.95	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JWCIM	256.0	Mb	133	66	1.7	1.95	-40.0	85.0	TFBGA (4X6)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JWCIMG	256.0	Mb	133	66	1.7	1.95	-40.0	85.0	TFBGA (4X6)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JWCIQ	256.0	Mb	133	-	1.7	1.95	-40.0	85.0	TFBGA (4X6)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JWCIQG	256.0	Mb	133	-	1.7	1.95	-40.0	85.0	TFBGA (4X6)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JWEAM	256.0	Mb	104	66	1.7	1.95	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JWEAMG	256.0	Mb	104	66	1.7	1.95	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JWEAQ	256.0	Mb	104	-	1.7	1.95	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JWEAQG	256.0	Mb	104	-	1.7	1.95	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JWEIM	256.0	Mb	133	66	1.7	1.95	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JWEIMG	256.0	Mb	133	66	1.7	1.95	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JWEIN	256.0	Mb	133	-	1.7	1.95	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		DRV=75%
W25Q256JWEING	256.0	Mb	133	-	1.7	1.95	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		DRV=75%
W25Q256JWEIQ	256.0	Mb	133	-	1.7	1.95	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JWEIQG	256.0	Mb	133	-	1.7	1.95	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JWEJQ	256.0	Mb	133	-	1.7	1.95	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JWEJQG	256.0	Mb	133	-	1.7	1.95	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JWESM	256.0	Mb	104	66	1.7	1.95	-40.0	125.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JWESMG	256.0	Mb	104	66	1.7	1.95	-40.0	125.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JWESQ	256.0	Mb	104	-	1.7	1.95	-40.0	125.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JWESQG	256.0	Mb	104	-	1.7	1.95	-40.0	125.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JWFAM	256.0	Mb	104	66	1.7	1.95	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q256JWFAMG	256.0	Mb	104	66	1.7	1.95	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q256JWFAQ	256.0	Mb	104	-	1.7	1.95	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q256JWFAQG	256.0	Mb	104	-	1.7	1.95	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q256JWFIM	256.0	Mb	133	66	1.7	1.95	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q256JWFIMG	256.0	Mb	133	66	1.7	1.95	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q256JWFIN	256.0	Mb	133	-	1.7	1.95	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		DRV=75%
W25Q256JWFING	256.0	Mb	133	-	1.7	1.95	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		DRV=75%
W25Q256JWFIQ	256.0	Mb	133	-	1.7	1.95	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q256JWFIQG	256.0	Mb	133	-	1.7	1.95	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q256JWFJQ	256.0	Mb	133	-	1.7	1.95	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q256JWFJQG	256.0	Mb	133	-	1.7	1.95	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q256JWFSM	256.0	Mb	104	66	1.7	1.95	-40.0	125.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q256JWFSMG	256.0	Mb	104	66	1.7	1.95	-40.0	125.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q256JWFSQ	256.0	Mb	104	-	1.7	1.95	-40.0	125.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q256JWFSQG	256.0	Mb	104	-	1.7	1.95	-40.0	125.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q256JWPAM	256.0	Mb	104	66	1.7	1.95	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JWPAMG	256.0	Mb	104	66	1.7	1.95	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JWPAQ	256.0	Mb	104	-	1.7	1.95	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JWPAQG	256.0	Mb	104	-	1.7	1.95	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q256JWPIM	256.0	Mb	133	66	1.7	1.95	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JWPIMG	256.0	Mb	133	66	1.7	1.95	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JWPIQ	256.0	Mb	133	-	1.7	1.95	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JWPIQG	256.0	Mb	133	-	1.7	1.95	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JWPJQ	256.0	Mb	133	-	1.7	1.95	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JWPJQG	256.0	Mb	133	-	1.7	1.95	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q256JWYIM	256.0	Mb	133	66	1.7	1.95	-40.0	85.0	WLCSP	32.0			SPI/Dual/Quad	P	-	No		-
W25Q256JWYIMG	256.0	Mb	133	66	1.7	1.95	-40.0	85.0	WLCSP	32.0			SPI/Dual/Quad	P	-	No		-
W25Q256JWYIQ	256.0	Mb	133	-	1.7	1.95	-40.0	85.0	WLCSP	32.0			SPI/Dual/Quad	P	-	No		-
W25Q256JWYIQG	256.0	Mb	133	-	1.7	1.95	-40.0	85.0	WLCSP	32.0			SPI/Dual/Quad	P	-	No		-
W25Q257JVEIQ	256.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		4-Byte Address Mode Default
W25Q257JVEIQG	256.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		4-Byte Address Mode Default
W25Q257JVFIQ	256.0	Mb	133	-	2.7	3.6	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		4-Byte Address Mode Default
W25Q257JVFIQG	256.0	Mb	133	-	2.7	3.6	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		4-Byte Address Mode Default
W25Q25PWBYIH	256.0	Mb	166	104	1.65	1.95	-40.0	85.0	WLCSP	32.0			SPI/Dual/Quad	UD	-	No	1bit	BUSY output
W25Q25PWBYIHG	256.0	Mb	166	104	1.65	1.95	-40.0	85.0	WLCSP	32.0			SPI/Dual/Quad	UD	-	No	1bit	BUSY output
W25Q25PWBYIJ	256.0	Mb	166	104	1.65	1.95	-40.0	85.0	WLCSP	32.0			SPI/Dual/Quad	UD	-	No	1bit	BUSY output
W25Q25PWBYIJG	256.0	Mb	166	104	1.65	1.95	-40.0	85.0	WLCSP	32.0			SPI/Dual/Quad	UD	-	No	1bit	BUSY output
W25Q25PWSFIM	256.0	Mb	166	104	1.65	1.95	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	S	-	No	1bit	-
W25Q25PWSFIMG	256.0	Mb	166	104	1.65	1.95	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	S	-	No	1bit	-
W25Q25PWSFIQ	256.0	Mb	166	104	1.65	1.95	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	S	-	No	1bit	-
W25Q25PWSFIQG	256.0	Mb	166	104	1.65	1.95	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	S	-	No	1bit	-
W25Q25PWSSIM	256.0	Mb	166	104	1.65	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	S	-	No	1bit	-
W25Q25PWSSIMG	256.0	Mb	166	104	1.65	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	S	-	No	1bit	-
W25Q25PWSSIQ	256.0	Mb	166	104	1.65	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	S	-	No	1bit	-
W25Q25PWSSIQG	256.0	Mb	166	104	1.65	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	S	-	No	1bit	-
W25Q25PWTBIM	256.0	Mb	166	104	1.65	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	S	-	No	1bit	-
W25Q25PWTBIMG	256.0	Mb	166	104	1.65	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	S	-	No	1bit	-
W25Q25PWTBIQ	256.0	Mb	166	104	1.65	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	S	-	No	1bit	-
W25Q25PWTBIQG	256.0	Mb	166	104	1.65	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	S	-	No	1bit	-
W25Q25PWXCIM	256.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	UD	-	No	1bit	-
W25Q25PWXCIMG	256.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	UD	-	No	1bit	-
W25Q25PWXCIQ	256.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	UD	-	No	1bit	-
W25Q25PWXCIQG	256.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	UD	-	No	1bit	-
W25Q25PWZEIM	256.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	S	-	No	1bit	-
W25Q25PWZEIMG	256.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	S	-	No	1bit	-
W25Q25PWZEIQ	256.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	S	-	No	1bit	-
W25Q25PWZEIQG	256.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	S	-	No	1bit	-
W25Q25PWZPIM	256.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	S	-	No	1bit	-
W25Q25PWZPIMG	256.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	S	-	No	1bit	-
W25Q25PWZPIQ	256.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	S	-	No	1bit	-
W25Q25PWZPIQG	256.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	S	-	No	1bit	-
W25Q25PYTBIJ	256.0	Mb	133	84	1.65	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	UD	-	No	1bit	1.2V I/O, RESET output
W25Q25PYTBIJG	256.0	Mb	133	84	1.65	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	UD	-	No	1bit	1.2V I/O, RESET output
W25Q25PYTBIM	256.0	Mb	133	84	1.65	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	UD	-	No	1bit	1.2V I/O, RESET output
W25Q25PYTBIMG	256.0	Mb	133	84	1.65	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	UD	-	No	1bit	1.2V I/O, RESET output
W25Q25PYTBIQ	256.0	Mb	133	84	1.65	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	UD	-	No	1bit	1.2V I/O, RESET output
W25Q25PYTBIQG	256.0	Mb	133	84	1.65	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	UD	-	No	1bit	1.2V I/O, RESET output
W25Q25PYZNIJ	256.0	Mb	133	84	1.65	1.95	-40.0	85.0	WQFN	12.0	5X6	MM^2	SPI/Dual/Quad	UD	-	No	1bit	1.2V I/O, RESET output
W25Q25PYZNIJG	256.0	Mb	133	84	1.65	1.95	-40.0	85.0	WQFN	12.0	5X6	MM^2	SPI/Dual/Quad	UD	-	No	1bit	1.2V I/O, RESET output
W25Q25PYZNIM	256.0	Mb	133	84	1.65	1.95	-40.0	85.0	WQFN	12.0	5X6	MM^2	SPI/Dual/Quad	UD	-	No	1bit	1.2V I/O, RESET output
W25Q25PYZNIMG	256.0	Mb	133	84	1.65	1.95	-40.0	85.0	WQFN	12.0	5X6	MM^2	SPI/Dual/Quad	UD	-	No	1bit	1.2V I/O, RESET output
W25Q25RVCBJM	256.0	Mb	133	104	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	UD	-	No	1bit	-
W25Q25RVCBJMG	256.0	Mb	133	104	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	UD	-	No	1bit	-
W25Q25RVCBJQ	256.0	Mb	133	-	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	UD	-	No	1bit	-
W25Q25RVCBJQG	256.0	Mb	133	-	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	UD	-	No	1bit	-
W25Q25RVCEJM	256.0	Mb	133	104	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	UD	-	No	1bit	-
W25Q25RVCEJMG	256.0	Mb	133	104	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	UD	-	No	1bit	-
W25Q25RVCEJQ	256.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	UD	-	No	1bit	-
W25Q25RVCEJQG	256.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	UD	-	No	1bit	-
W25Q25RVCFJM	256.0	Mb	133	104	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	UD	-	No	1bit	-
W25Q25RVCFJMG	256.0	Mb	133	104	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	UD	-	No	1bit	-
W25Q25RVCFJQ	256.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	UD	-	No	1bit	-
W25Q25RVCFJQG	256.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	UD	-	No	1bit	-
W25Q25RVCPJM	256.0	Mb	133	104	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	UD	-	No	1bit	-
W25Q25RVCPJMG	256.0	Mb	133	104	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	UD	-	No	1bit	-
W25Q25RVCPJQ	256.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	UD	-	No	1bit	-
W25Q25RVCPJQG	256.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	UD	-	No	1bit	-
W25Q32JVSFAM	32.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVSFAMG	32.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVSFAQ	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVSFAQG	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVSFIM	32.0	Mb	133	66	2.7	3.6	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32JVSFIMG	32.0	Mb	133	66	2.7	3.6	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32JVSFIQ	32.0	Mb	133	-	2.7	3.6	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32JVSFIQG	32.0	Mb	133	-	2.7	3.6	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32JVSFJM	32.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32JVSFJMG	32.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32JVSFJQ	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32JVSFJQG	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32JVSFSM	32.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVSFSMG	32.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVSFSQ	32.0	Mb	133	-	2.7	3.6	-40.0	125.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVSFSQG	32.0	Mb	133	-	2.7	3.6	-40.0	125.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVSNAM	32.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVSNAMG	32.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVSNAQ	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVSNAQG	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVSNIM	32.0	Mb	133	66	2.7	3.6	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32JVSNIMG	32.0	Mb	133	66	2.7	3.6	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32JVSNIQ	32.0	Mb	133	-	2.7	3.6	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32JVSNIQG	32.0	Mb	133	-	2.7	3.6	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32JVSNJM	32.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32JVSNJMG	32.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32JVSNJQ	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32JVSNJQG	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32JVSNSM	32.0	Mb	133	66	2.7	3.6	-40.0	125.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVSNSMG	32.0	Mb	133	66	2.7	3.6	-40.0	125.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVSNSQ	32.0	Mb	133	-	2.7	3.6	-40.0	125.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVSNSQG	32.0	Mb	133	-	2.7	3.6	-40.0	125.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVSSAM	32.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVSSAMG	32.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVSSAQ	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVSSAQG	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVSSIM	32.0	Mb	133	66	2.7	3.6	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32JVSSIMG	32.0	Mb	133	66	2.7	3.6	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32JVSSIQ	32.0	Mb	133	-	2.7	3.6	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32JVSSIQG	32.0	Mb	133	-	2.7	3.6	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32JVSSJM	32.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32JVSSJMG	32.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32JVSSJQ	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32JVSSJQG	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32JVSSSM	32.0	Mb	133	66	2.7	3.6	-40.0	125.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVSSSMG	32.0	Mb	133	66	2.7	3.6	-40.0	125.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVSSSQ	32.0	Mb	133	-	2.7	3.6	-40.0	125.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVSSSQG	32.0	Mb	133	-	2.7	3.6	-40.0	125.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVTBAM	32.0	Mb	133	66	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVTBAMG	32.0	Mb	133	66	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVTBAQ	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVTBAQG	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVTBIM	32.0	Mb	133	66	2.7	3.6	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVTBIMG	32.0	Mb	133	66	2.7	3.6	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVTBIQ	32.0	Mb	133	-	2.7	3.6	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVTBIQG	32.0	Mb	133	-	2.7	3.6	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVTBJM	32.0	Mb	133	66	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVTBJMG	32.0	Mb	133	66	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVTBJQ	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVTBJQG	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVTBSM	32.0	Mb	133	66	2.7	3.6	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVTBSMG	32.0	Mb	133	66	2.7	3.6	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVTBSQ	32.0	Mb	133	-	2.7	3.6	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVTBSQG	32.0	Mb	133	-	2.7	3.6	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVTCIM	32.0	Mb	133	66	2.7	3.6	-40.0	85.0	TFBGA (4X6)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVTCIMG	32.0	Mb	133	66	2.7	3.6	-40.0	85.0	TFBGA (4X6)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVTCIQ	32.0	Mb	133	-	2.7	3.6	-40.0	85.0	TFBGA (4X6)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVTCIQG	32.0	Mb	133	-	2.7	3.6	-40.0	85.0	TFBGA (4X6)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVTCJM	32.0	Mb	133	66	2.7	3.6	-40.0	105.0	TFBGA (4X6)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVTCJMG	32.0	Mb	133	66	2.7	3.6	-40.0	105.0	TFBGA (4X6)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVTCJQ	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	TFBGA (4X6)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVTCJQG	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	TFBGA (4X6)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVUUAM	32.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVUUAMG	32.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVUUAQ	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVUUAQG	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVUUIM	32.0	Mb	133	66	2.7	3.6	-40.0	85.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVUUIMG	32.0	Mb	133	66	2.7	3.6	-40.0	85.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVUUIQ	32.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVUUIQG	32.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVUUJM	32.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVUUJMG	32.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVUUJQ	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVUUJQG	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVUUSM	32.0	Mb	133	66	2.7	3.6	-40.0	125.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVUUSMG	32.0	Mb	133	66	2.7	3.6	-40.0	125.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVUUSQ	32.0	Mb	133	-	2.7	3.6	-40.0	125.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVUUSQG	32.0	Mb	133	-	2.7	3.6	-40.0	125.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVXGAM	32.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVXGAMG	32.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVXGAQ	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVXGAQG	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVXGIM	32.0	Mb	133	66	2.7	3.6	-40.0	85.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVXGIMG	32.0	Mb	133	66	2.7	3.6	-40.0	85.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVXGIQ	32.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVXGIQG	32.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVXGJM	32.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVXGJMG	32.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVXGJQ	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVXGJQG	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVXGSM	32.0	Mb	133	66	2.7	3.6	-40.0	125.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVXGSMG	32.0	Mb	133	66	2.7	3.6	-40.0	125.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVXGSQ	32.0	Mb	133	-	2.7	3.6	-40.0	125.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVXGSQG	32.0	Mb	133	-	2.7	3.6	-40.0	125.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVZEAQ	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVZEAQG	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVZEIQ	32.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVZEIQG	32.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVZESQ	32.0	Mb	133	-	2.7	3.6	-40.0	125.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVZESQG	32.0	Mb	133	-	2.7	3.6	-40.0	125.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVZPAM	32.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVZPAMG	32.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVZPAQ	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVZPAQG	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVZPIM	32.0	Mb	133	66	2.7	3.6	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVZPIMG	32.0	Mb	133	66	2.7	3.6	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVZPIQ	32.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVZPIQG	32.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVZPJM	32.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVZPJMG	32.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVZPJQ	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVZPJQG	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JVZPSM	32.0	Mb	133	66	2.7	3.6	-40.0	125.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVZPSMG	32.0	Mb	133	66	2.7	3.6	-40.0	125.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVZPSQ	32.0	Mb	133	-	2.7	3.6	-40.0	125.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JVZPSQG	32.0	Mb	133	-	2.7	3.6	-40.0	125.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWBYIM	32.0	Mb	133	66	1.7	1.95	-40.0	85.0	WLCSP	12.0			SPI/Dual/Quad	P	-	No		-
W25Q32JWBYIMG	32.0	Mb	133	66	1.7	1.95	-40.0	85.0	WLCSP	12.0			SPI/Dual/Quad	P	-	No		-
W25Q32JWBYIQ	32.0	Mb	133	-	1.7	1.95	-40.0	85.0	WLCSP	12.0			SPI/Dual/Quad	P	-	No		-
W25Q32JWBYIQG	32.0	Mb	133	-	1.7	1.95	-40.0	85.0	WLCSP	12.0			SPI/Dual/Quad	P	-	No		-
W25Q32JWSNAM	32.0	Mb	104	66	1.7	1.95	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWSNAMG	32.0	Mb	104	66	1.7	1.95	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWSNAQ	32.0	Mb	104	-	1.7	1.95	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWSNAQG	32.0	Mb	104	-	1.7	1.95	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWSNIM	32.0	Mb	133	66	1.7	1.95	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32JWSNIMG	32.0	Mb	133	66	1.7	1.95	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32JWSNIQ	32.0	Mb	133	-	1.7	1.95	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32JWSNIQG	32.0	Mb	133	-	1.7	1.95	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32JWSNJQ	32.0	Mb	133	-	1.7	1.95	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32JWSNJQG	32.0	Mb	133	-	1.7	1.95	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32JWSNSM	32.0	Mb	104	66	1.7	1.95	-40.0	125.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWSNSMG	32.0	Mb	104	66	1.7	1.95	-40.0	125.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWSNSQ	32.0	Mb	104	-	1.7	1.95	-40.0	125.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWSNSQG	32.0	Mb	104	-	1.7	1.95	-40.0	125.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWSSAM	32.0	Mb	104	66	1.7	1.95	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWSSAMG	32.0	Mb	104	66	1.7	1.95	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWSSAQ	32.0	Mb	104	-	1.7	1.95	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWSSAQG	32.0	Mb	104	-	1.7	1.95	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWSSIM	32.0	Mb	133	66	1.7	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32JWSSIMG	32.0	Mb	133	66	1.7	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32JWSSIQ	32.0	Mb	133	-	1.7	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32JWSSIQG	32.0	Mb	133	-	1.7	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32JWSSJQ	32.0	Mb	133	-	1.7	1.95	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32JWSSJQG	32.0	Mb	133	-	1.7	1.95	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32JWSSSM	32.0	Mb	104	66	1.7	1.95	-40.0	125.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWSSSMG	32.0	Mb	104	66	1.7	1.95	-40.0	125.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWSSSQ	32.0	Mb	104	-	1.7	1.95	-40.0	125.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWSSSQG	32.0	Mb	104	-	1.7	1.95	-40.0	125.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWTBAM	32.0	Mb	104	66	1.7	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWTBAMG	32.0	Mb	104	66	1.7	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWTBAQ	32.0	Mb	104	-	1.7	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWTBAQG	32.0	Mb	104	-	1.7	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWTBIQ	32.0	Mb	133	-	1.7	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JWTBIQG	32.0	Mb	133	-	1.7	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JWTBJQ	32.0	Mb	133	-	1.7	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JWTBJQG	32.0	Mb	133	-	1.7	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JWTBSM	32.0	Mb	104	66	1.7	1.95	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWTBSMG	32.0	Mb	104	66	1.7	1.95	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWTBSQ	32.0	Mb	104	-	1.7	1.95	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWTBSQG	32.0	Mb	104	-	1.7	1.95	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWTCIQ	32.0	Mb	133	-	1.7	1.95	-40.0	85.0	TFBGA (4X6)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JWTCIQG	32.0	Mb	133	-	1.7	1.95	-40.0	85.0	TFBGA (4X6)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JWUUAM	32.0	Mb	104	66	1.7	1.95	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWUUAMG	32.0	Mb	104	66	1.7	1.95	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWUUAQ	32.0	Mb	104	-	1.7	1.95	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWUUAQG	32.0	Mb	104	-	1.7	1.95	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWUUIM	32.0	Mb	133	66	1.7	1.95	-40.0	85.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JWUUIMG	32.0	Mb	133	66	1.7	1.95	-40.0	85.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JWUUIQ	32.0	Mb	133	-	1.7	1.95	-40.0	85.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JWUUIQG	32.0	Mb	133	-	1.7	1.95	-40.0	85.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JWUUJM	32.0	Mb	133	-	1.7	1.95	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JWUUJMG	32.0	Mb	133	-	1.7	1.95	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JWUUJQ	32.0	Mb	133	-	1.7	1.95	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JWUUJQG	32.0	Mb	133	-	1.7	1.95	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JWUUSM	32.0	Mb	104	66	1.7	1.95	-40.0	125.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWUUSMG	32.0	Mb	104	66	1.7	1.95	-40.0	125.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWUUSQ	32.0	Mb	104	-	1.7	1.95	-40.0	125.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWUUSQG	32.0	Mb	104	-	1.7	1.95	-40.0	125.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWXGAM	32.0	Mb	104	66	1.7	1.95	-40.0	105.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWXGAMG	32.0	Mb	104	66	1.7	1.95	-40.0	105.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWXGAQ	32.0	Mb	104	-	1.7	1.95	-40.0	105.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWXGAQG	32.0	Mb	104	-	1.7	1.95	-40.0	105.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWXGIM	32.0	Mb	133	66	1.7	1.95	-40.0	85.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JWXGIMG	32.0	Mb	133	66	1.7	1.95	-40.0	85.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JWXGIQ	32.0	Mb	133	-	1.7	1.95	-40.0	85.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JWXGIQG	32.0	Mb	133	-	1.7	1.95	-40.0	85.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JWXGSM	32.0	Mb	104	66	1.7	1.95	-40.0	125.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWXGSMG	32.0	Mb	104	66	1.7	1.95	-40.0	125.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWXGSQ	32.0	Mb	104	-	1.7	1.95	-40.0	125.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWXGSQG	32.0	Mb	104	-	1.7	1.95	-40.0	125.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWZPAM	32.0	Mb	104	66	1.7	1.95	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWZPAMG	32.0	Mb	104	66	1.7	1.95	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWZPAQ	32.0	Mb	104	-	1.7	1.95	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWZPAQG	32.0	Mb	104	-	1.7	1.95	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWZPIM	32.0	Mb	133	66	1.7	1.95	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JWZPIMG	32.0	Mb	133	66	1.7	1.95	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JWZPIQ	32.0	Mb	133	-	1.7	1.95	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JWZPIQG	32.0	Mb	133	-	1.7	1.95	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JWZPJQ	32.0	Mb	133	-	1.7	1.95	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JWZPJQG	32.0	Mb	133	-	1.7	1.95	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32JWZPSM	32.0	Mb	104	66	1.7	1.95	-40.0	125.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWZPSMG	32.0	Mb	104	66	1.7	1.95	-40.0	125.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWZPSQ	32.0	Mb	104	-	1.7	1.95	-40.0	125.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32JWZPSQG	32.0	Mb	104	-	1.7	1.95	-40.0	125.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q32RVCNJM	32.0	Mb	133	84	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32RVCNJMG	32.0	Mb	133	84	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32RVCNJQ	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32RVCNJQG	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32RVCPJM	32.0	Mb	133	84	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32RVCPJMG	32.0	Mb	133	84	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32RVCPJQ	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32RVCPJQG	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32RVCSJM	32.0	Mb	133	84	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32RVCSJMG	32.0	Mb	133	84	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32RVCSJQ	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32RVCSJQG	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q32RVUUJM	32.0	Mb	133	84	2.7	3.6	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32RVUUJMG	32.0	Mb	133	84	2.7	3.6	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32RVUUJQ	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32RVUUJQG	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32RVXHJM	32.0	Mb	133	84	2.7	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32RVXHJMG	32.0	Mb	133	84	2.7	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32RVXHJQ	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q32RVXHJQG	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q33PWSNIM	32.0	Mb	166	104	1.65	1.95	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	S	-	No		-
W25Q33PWSNIMG	32.0	Mb	166	104	1.65	1.95	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	S	-	No		-
W25Q33PWSNIQ	32.0	Mb	166	-	1.65	1.95	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	S	-	No		-
W25Q33PWSNIQG	32.0	Mb	166	-	1.65	1.95	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	S	-	No		-
W25Q33PWSSIM	32.0	Mb	166	104	1.65	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	S	-	No		-
W25Q33PWSSIMG	32.0	Mb	166	104	1.65	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	S	-	No		-
W25Q33PWSSIQ	32.0	Mb	166	-	1.65	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	S	-	No		-
W25Q33PWSSIQG	32.0	Mb	166	-	1.65	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	S	-	No		-
W25Q33PWUUIM	32.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q33PWUUIMG	32.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q33PWUUIQ	32.0	Mb	166	-	1.65	1.95	-40.0	85.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q33PWUUIQG	32.0	Mb	166	-	1.65	1.95	-40.0	85.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q33PWXHIM	32.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q33PWXHIMG	32.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q33PWXHIQ	32.0	Mb	166	-	1.65	1.95	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q33PWXHIQG	32.0	Mb	166	-	1.65	1.95	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q33RVSNJM	32.0	Mb	133	104	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	UD	-	No		-
W25Q33RVSNJMG	32.0	Mb	133	104	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	UD	-	No		-
W25Q33RVSNJQ	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	UD	-	No		-
W25Q33RVSNJQG	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	UD	-	No		-
W25Q33RVSSJM	32.0	Mb	133	104	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	UD	-	No		-
W25Q33RVSSJMG	32.0	Mb	133	104	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	UD	-	No		-
W25Q33RVSSJQ	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	UD	-	No		-
W25Q33RVSSJQG	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	UD	-	No		-
W25Q33RVUUJM	32.0	Mb	133	104	2.7	3.6	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	UD	-	No		-
W25Q33RVUUJMG	32.0	Mb	133	104	2.7	3.6	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	UD	-	No		-
W25Q33RVUUJQ	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	UD	-	No		-
W25Q33RVUUJQG	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	UD	-	No		-
W25Q33RVXGJM	32.0	Mb	133	104	2.7	3.6	-40.0	105.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	UD	-	No		-
W25Q33RVXGJMG	32.0	Mb	133	104	2.7	3.6	-40.0	105.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	UD	-	No		-
W25Q33RVXGJQ	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	UD	-	No		-
W25Q33RVXGJQG	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	UD	-	No		-
W25Q33RVZNJM			133	104	2.7	3.6							SPI/Dual/Quad	UD	-	No		-
W25Q33RVZNJMG			133	104	2.7	3.6							SPI/Dual/Quad	UD	-	No		-
W25Q33RVZNJQ			133	-	2.7	3.6							SPI/Dual/Quad	UD	-	No		-
W25Q33RVZNJQG			133	-	2.7	3.6							SPI/Dual/Quad	UD	-	No		-
W25Q33RVZPJM	32.0	Mb	133	104	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	UD	-	No		-
W25Q33RVZPJMG	32.0	Mb	133	104	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	UD	-	No		-
W25Q33RVZPJQ	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	UD	-	No		-
W25Q33RVZPJQG	32.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	UD	-	No		-
W25Q40CLSNIG	4.0	Mb	104	-	2.3	3.6	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q40CLSNIGG	4.0	Mb	104	-	2.3	3.6	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q40CLSSIG	4.0	Mb	104	-	2.3	3.6	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q40CLSSIGG	4.0	Mb	104	-	2.3	3.6	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q40CLUXIG	4.0	Mb	104	-	2.3	3.6	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q40CLUXIGG	4.0	Mb	104	-	2.3	3.6	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q40CVSNAG	4.0	Mb	80	-	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q40CVSNAGG	4.0	Mb	80	-	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q40CVSNBG	4.0	Mb	80	-	2.7	3.6	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q40CVSNBGG	4.0	Mb	80	-	2.7	3.6	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q40CVSNSG	4.0	Mb	80	-	2.7	3.6	-40.0	125.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q40CVSNSGG	4.0	Mb	80	-	2.7	3.6	-40.0	125.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q40CVSSSG	4.0	Mb	80	-	2.7	3.6	-40.0	125.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q40CVSSSGG	4.0	Mb	80	-	2.7	3.6	-40.0	125.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q40CVUXAG	4.0	Mb	80	-	2.7	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q40CVUXAGG	4.0	Mb	80	-	2.7	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q40CVUXBG	4.0	Mb	80	-	2.7	3.6	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q40CVUXBGG	4.0	Mb	80	-	2.7	3.6	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q40CVUXSG	4.0	Mb	80	-	2.7	3.6	-40.0	125.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q40CVUXSGG	4.0	Mb	80	-	2.7	3.6	-40.0	125.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q40CVZPAG	4.0	Mb	80	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q40CVZPAGG	4.0	Mb	80	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q40CVZPBG	4.0	Mb	80	-	2.7	3.6	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q40CVZPBGG	4.0	Mb	80	-	2.7	3.6	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q40CVZPSG	4.0	Mb	80	-	2.7	3.6	-40.0	125.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q40CVZPSGG	4.0	Mb	80	-	2.7	3.6	-40.0	125.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q40EWBYIG	4.0	Mb	104	-	1.65	1.95	-40.0	85.0	WLCSP	8.0			SPI/Dual/Quad	P	-	No		-
W25Q40EWBYIGG	4.0	Mb	104	-	1.65	1.95	-40.0	85.0	WLCSP	8.0			SPI/Dual/Quad	P	-	No		-
W25Q40EWSNIG	4.0	Mb	104	-	1.65	1.95	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q40EWSNIGG	4.0	Mb	104	-	1.65	1.95	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q40EWSNJG	4.0	Mb	104	-	1.65	1.95	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q40EWSNJGG	4.0	Mb	104	-	1.65	1.95	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q40EWSSIG	4.0	Mb	104	-	1.65	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q40EWSSIGG	4.0	Mb	104	-	1.65	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q40EWUXIE	4.0	Mb	104	-	1.65	1.95	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q40EWUXIEG	4.0	Mb	104	-	1.65	1.95	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q40EWUXJE	4.0	Mb	104	-	1.65	1.95	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q40EWUXJEG	4.0	Mb	104	-	1.65	1.95	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q40RLSNJM	4.0	Mb	133	84	2.3	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q40RLSNJMG	4.0	Mb	133	84	2.3	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q40RLSNJQ	4.0	Mb	133	-	2.3	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q40RLSNJQG	4.0	Mb	133	-	2.3	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q40RLSSJM	4.0	Mb	133	84	2.3	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q40RLSSJMG	4.0	Mb	133	84	2.3	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q40RLSSJQ	4.0	Mb	133	-	2.3	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q40RLSSJQG	4.0	Mb	133	-	2.3	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q40RLXHJM	4.0	Mb	133	84	2.3	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q40RLXHJMG	4.0	Mb	133	84	2.3	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q40RLXHJQ	4.0	Mb	133	-	2.3	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q40RLXHJQG	4.0	Mb	133	-	2.3	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q40RLZPJM	4.0	Mb	133	84	2.3	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q40RLZPJMG	4.0	Mb	133	84	2.3	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q40RLZPJQ	4.0	Mb	133	-	2.3	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q40RLZPJQG	4.0	Mb	133	-	2.3	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q40RVSNJM	4.0	Mb	133	84	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q40RVSNJMG	4.0	Mb	133	84	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q40RVSNJQ	4.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q40RVSNJQG	4.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q40RVSSJM	4.0	Mb	133	84	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q40RVSSJMG	4.0	Mb	133	84	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q40RVSSJQ	4.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q40RVSSJQG	4.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q40RVXHJM	4.0	Mb	133	84	2.7	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q40RVXHJMG	4.0	Mb	133	84	2.7	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q40RVXHJQ	4.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q40RVXHJQG	4.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q40RVZPJM	4.0	Mb	133	84	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q40RVZPJMG	4.0	Mb	133	84	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q40RVZPJQ	4.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q40RVZPJQG	4.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q41EWSNAG	4.0	Mb	104	-	1.65	1.95	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q41EWSNAGG	4.0	Mb	104	-	1.65	1.95	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q41EWSNSG	4.0	Mb	104	-	1.65	1.95	-40.0	125.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q41EWSNSGG	4.0	Mb	104	-	1.65	1.95	-40.0	125.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q41EWXHAG	4.0	Mb	104	-	1.65	1.95	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q41EWXHAGG	4.0	Mb	104	-	1.65	1.95	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q41EWXHSG	4.0	Mb	104	-	1.65	1.95	-40.0	125.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q41EWXHSGG	4.0	Mb	104	-	1.65	1.95	-40.0	125.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q512JVBIM	512.0	Mb	133	66	2.7	3.6	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q512JVBIMG	512.0	Mb	133	66	2.7	3.6	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q512JVBIQ	512.0	Mb	133	-	2.7	3.6	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q512JVBIQG	512.0	Mb	133	-	2.7	3.6	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q512JVBJQ	512.0	Mb	133	-	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q512JVBJQG	512.0	Mb	133	-	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q512JVEIM	512.0	Mb	133	66	2.7	3.6	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q512JVEIMG	512.0	Mb	133	66	2.7	3.6	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q512JVEIN	512.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		DRV=75%
W25Q512JVEING	512.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		DRV=75%
W25Q512JVEIQ	512.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q512JVEIQG	512.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q512JVEJQ	512.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q512JVEJQG	512.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q512JVFIM	512.0	Mb	133	66	2.7	3.6	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q512JVFIMG	512.0	Mb	133	66	2.7	3.6	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q512JVFIN	512.0	Mb	133	-	2.7	3.6	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		DRV=75%
W25Q512JVFING	512.0	Mb	133	-	2.7	3.6	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		DRV=75%
W25Q512JVFIQ	512.0	Mb	133	-	2.7	3.6	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q512JVFIQG	512.0	Mb	133	-	2.7	3.6	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q512JVFJQ	512.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q512JVFJQG	512.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q512NWBIA	512.0	Mb	133	-	1.65	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q512NWBIAG	512.0	Mb	133	-	1.65	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q512NWBIM	512.0	Mb	133	84	1.65	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q512NWBIMG	512.0	Mb	133	84	1.65	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q512NWBIQ	512.0	Mb	133	-	1.65	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q512NWBIQG	512.0	Mb	133	-	1.65	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q512NWBIS	512.0	Mb	133	84	1.65	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q512NWBISG	512.0	Mb	133	84	1.65	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q512NWBJM	512.0	Mb	133	-	1.65	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q512NWBJMG	512.0	Mb	133	-	1.65	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q512NWBJQ	512.0	Mb	133	-	1.65	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q512NWBJQG	512.0	Mb	133	-	1.65	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q512NWEIM	512.0	Mb	133	84	1.65	1.95	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q512NWEIMG	512.0	Mb	133	84	1.65	1.95	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q512NWEIN	512.0	Mb	133	-	1.65	1.95	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		DRV=75%
W25Q512NWEING	512.0	Mb	133	-	1.65	1.95	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		DRV=75%
W25Q512NWEIQ	512.0	Mb	133	-	1.65	1.95	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q512NWEIQG	512.0	Mb	133	-	1.65	1.95	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q512NWEJM	512.0	Mb	133	-	1.65	1.95	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q512NWEJMG	512.0	Mb	133	-	1.65	1.95	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q512NWFIA	512.0	Mb	133	-	1.65	1.95	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q512NWFIAG	512.0	Mb	133	-	1.65	1.95	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q512NWFIM	512.0	Mb	133	84	1.65	1.95	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q512NWFIMG	512.0	Mb	133	84	1.65	1.95	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q512NWFIN	512.0	Mb	133	-	1.65	1.95	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		DRV=75%
W25Q512NWFING	512.0	Mb	133	-	1.65	1.95	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		DRV=75%
W25Q512NWFIQ	512.0	Mb	133	-	1.65	1.95	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q512NWFIQG	512.0	Mb	133	-	1.65	1.95	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q512NWFJM	512.0	Mb	133	-	1.65	1.95	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q512NWFJMG	512.0	Mb	133	-	1.65	1.95	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q512NWFJQ	512.0	Mb	133	-	1.65	1.95	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q512NWFJQG	512.0	Mb	133	-	1.65	1.95	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q512NWYIM	512.0	Mb	133	84	1.65	1.95	-40.0	85.0	WLCSP	88.0			SPI/Dual/Quad	P	-	No		-
W25Q512NWYIMG	512.0	Mb	133	84	1.65	1.95	-40.0	85.0	WLCSP	88.0			SPI/Dual/Quad	P	-	No		-
W25Q512NWYIQ	512.0	Mb	133	-	1.65	1.95	-40.0	85.0	WLCSP	88.0			SPI/Dual/Quad	P	-	No		-
W25Q512NWYIQG	512.0	Mb	133	-	1.65	1.95	-40.0	85.0	WLCSP	88.0			SPI/Dual/Quad	P	-	No		-
W25Q51RVCBJM	512.0	Mb	133	104	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No	1bit	-
W25Q51RVCBJMG	512.0	Mb	133	104	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No	1bit	-
W25Q51RVCBJQ	512.0	Mb	133	-	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No	1bit	-
W25Q51RVCBJQG	512.0	Mb	133	-	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No	1bit	-
W25Q51RVCEJM	512.0	Mb	133	104	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No	1bit	-
W25Q51RVCEJMG	512.0	Mb	133	104	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No	1bit	-
W25Q51RVCEJQ	512.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No	1bit	-
W25Q51RVCEJQG	512.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No	1bit	-
W25Q51RVCFJM	512.0	Mb	133	104	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No	1bit	-
W25Q51RVCFJMG	512.0	Mb	133	104	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No	1bit	-
W25Q51RVCFJQ	512.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No	1bit	-
W25Q51RVCFJQG	512.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No	1bit	-
W25Q64JVBYIQ	64.0	Mb	133	-	2.7	3.6	-40.0	85.0	WLCSP	12.0			SPI/Dual/Quad	P	-	No		-
W25Q64JVBYIQG	64.0	Mb	133	-	2.7	3.6	-40.0	85.0	WLCSP	12.0			SPI/Dual/Quad	P	-	No		-
W25Q64JVSFAM	64.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVSFAMG	64.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVSFAQ	64.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVSFAQG	64.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVSFIM	64.0	Mb	133	66	2.7	3.6	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q64JVSFIMG	64.0	Mb	133	66	2.7	3.6	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q64JVSFIQ	64.0	Mb	133	-	2.7	3.6	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q64JVSFIQG	64.0	Mb	133	-	2.7	3.6	-40.0	85.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q64JVSFJM	64.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q64JVSFJMG	64.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q64JVSFJQ	64.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q64JVSFJQG	64.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	16.0	300	MIL	SPI/Dual/Quad	P	-	No		-
W25Q64JVSFSM	64.0	Mb	133	66	2.7	3.6	-40.0	125.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVSFSMG	64.0	Mb	133	66	2.7	3.6	-40.0	125.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVSFSQ	64.0	Mb	133	-	2.7	3.6	-40.0	125.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVSFSQG	64.0	Mb	133	-	2.7	3.6	-40.0	125.0	SOP	16.0	300	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVSSAM	64.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVSSAMG	64.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVSSAQ	64.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVSSAQG	64.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVSSIM	64.0	Mb	133	66	2.7	3.6	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q64JVSSIMG	64.0	Mb	133	66	2.7	3.6	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q64JVSSIQ	64.0	Mb	133	-	2.7	3.6	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q64JVSSIQG	64.0	Mb	133	-	2.7	3.6	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q64JVSSJM	64.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q64JVSSJMG	64.0	Mb	133	66	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q64JVSSJQ	64.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q64JVSSJQG	64.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q64JVSSSM	64.0	Mb	133	66	2.7	3.6	-40.0	125.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVSSSMG	64.0	Mb	133	66	2.7	3.6	-40.0	125.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVSSSQ	64.0	Mb	133	-	2.7	3.6	-40.0	125.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVSSSQG	64.0	Mb	133	-	2.7	3.6	-40.0	125.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVTBAQ	64.0	Mb	133	-	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVTBAQG	64.0	Mb	133	-	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVTBIM	64.0	Mb	133	66	2.7	3.6	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JVTBIMG	64.0	Mb	133	66	2.7	3.6	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JVTBIQ	64.0	Mb	133	-	2.7	3.6	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JVTBIQG	64.0	Mb	133	-	2.7	3.6	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JVTBSQ	64.0	Mb	133	-	2.7	3.6	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVTBSQG	64.0	Mb	133	-	2.7	3.6	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVTCAQ	64.0	Mb	133	-	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVTCAQG	64.0	Mb	133	-	2.7	3.6	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVTCIQ	64.0	Mb	133	-	2.7	3.6	-40.0	85.0	TFBGA (4X6)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JVTCIQG	64.0	Mb	133	-	2.7	3.6	-40.0	85.0	TFBGA (4X6)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JVTCJQ	64.0	Mb	133	-	2.7	3.6	-40.0	105.0	TFBGA (4X6)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JVTCJQG	64.0	Mb	133	-	2.7	3.6	-40.0	105.0	TFBGA (4X6)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JVTCSQ	64.0	Mb	133	-	2.7	3.6	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVTCSQG	64.0	Mb	133	-	2.7	3.6	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVXGAM	64.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVXGAMG	64.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVXGAQ	64.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVXGAQG	64.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVXGIM	64.0	Mb	133	66	2.7	3.6	-40.0	85.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JVXGIMG	64.0	Mb	133	66	2.7	3.6	-40.0	85.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JVXGIQ	64.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JVXGIQG	64.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JVXGJM	64.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JVXGJMG	64.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JVXGJQ	64.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JVXGJQG	64.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JVXGSM	64.0	Mb	133	66	2.7	3.6	-40.0	125.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVXGSMG	64.0	Mb	133	66	2.7	3.6	-40.0	125.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVXGSQ	64.0	Mb	133	-	2.7	3.6	-40.0	125.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVXGSQG	64.0	Mb	133	-	2.7	3.6	-40.0	125.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVZEAM	64.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVZEAMG	64.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVZEAQ	64.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVZEAQG	64.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVZEIM	64.0	Mb	133	66	2.7	3.6	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JVZEIMG	64.0	Mb	133	66	2.7	3.6	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JVZEIQ	64.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JVZEIQG	64.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JVZEJM	64.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JVZEJMG	64.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JVZEJQ	64.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JVZEJQG	64.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JVZESM	64.0	Mb	133	66	2.7	3.6	-40.0	125.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVZESMG	64.0	Mb	133	66	2.7	3.6	-40.0	125.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVZESQ	64.0	Mb	133	-	2.7	3.6	-40.0	125.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVZESQG	64.0	Mb	133	-	2.7	3.6	-40.0	125.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVZPAM	64.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVZPAMG	64.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVZPAQ	64.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVZPAQG	64.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVZPIM	64.0	Mb	133	66	2.7	3.6	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JVZPIMG	64.0	Mb	133	66	2.7	3.6	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JVZPIQ	64.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JVZPIQG	64.0	Mb	133	-	2.7	3.6	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JVZPJM	64.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JVZPJMG	64.0	Mb	133	66	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JVZPJQ	64.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JVZPJQG	64.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JVZPSM	64.0	Mb	133	66	2.7	3.6	-40.0	125.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVZPSMG	64.0	Mb	133	66	2.7	3.6	-40.0	125.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVZPSQ	64.0	Mb	133	-	2.7	3.6	-40.0	125.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JVZPSQG	64.0	Mb	133	-	2.7	3.6	-40.0	125.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JWBYIM	64.0	Mb	133	66	1.7	1.95	-40.0	85.0	WLCSP	12.0			SPI/Dual/Quad	P	-	No		-
W25Q64JWBYIMG	64.0	Mb	133	66	1.7	1.95	-40.0	85.0	WLCSP	12.0			SPI/Dual/Quad	P	-	No		-
W25Q64JWBYIQ	64.0	Mb	133	-	1.7	1.95	-40.0	85.0	WLCSP	12.0			SPI/Dual/Quad	P	-	No		-
W25Q64JWBYIQG	64.0	Mb	133	-	1.7	1.95	-40.0	85.0	WLCSP	12.0			SPI/Dual/Quad	P	-	No		-
W25Q64JWBYJQ	64.0	Mb	133	-	1.7	1.95	-40.0	105.0	WLCSP	12.0			SPI/Dual/Quad	P	-	No		-
W25Q64JWBYJQG	64.0	Mb	133	-	1.7	1.95	-40.0	105.0	WLCSP	12.0			SPI/Dual/Quad	P	-	No		-
W25Q64JWSSAM	64.0	Mb	104	66	1.7	1.95	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q64JWSSAMG	64.0	Mb	104	66	1.7	1.95	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q64JWSSAQ	64.0	Mb	104	-	1.7	1.95	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q64JWSSAQG	64.0	Mb	104	-	1.7	1.95	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q64JWSSIM	64.0	Mb	133	66	1.7	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q64JWSSIMG	64.0	Mb	133	66	1.7	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q64JWSSIN	64.0	Mb	133	-	1.7	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		DRV=75%
W25Q64JWSSING	64.0	Mb	133	-	1.7	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		DRV=75%
W25Q64JWSSIQ	64.0	Mb	133	-	1.7	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q64JWSSIQG	64.0	Mb	133	-	1.7	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q64JWSSJQ	64.0	Mb	133	-	1.7	1.95	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q64JWSSJQG	64.0	Mb	133	-	1.7	1.95	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q64JWSSSM	64.0	Mb	104	66	1.7	1.95	-40.0	125.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q64JWSSSMG	64.0	Mb	104	66	1.7	1.95	-40.0	125.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q64JWSSSQ	64.0	Mb	104	-	1.7	1.95	-40.0	125.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q64JWSSSQG	64.0	Mb	104	-	1.7	1.95	-40.0	125.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q64JWTBAM	64.0	Mb	104	66	1.7	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JWTBAMG	64.0	Mb	104	66	1.7	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JWTBAQ	64.0	Mb	104	-	1.7	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JWTBAQG	64.0	Mb	104	-	1.7	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JWTBIM	64.0	Mb	133	66	1.7	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JWTBIMG	64.0	Mb	133	66	1.7	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JWTBIQ	64.0	Mb	133	-	1.7	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JWTBIQG	64.0	Mb	133	-	1.7	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JWTBJQ	64.0	Mb	133	-	1.7	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JWTBJQG	64.0	Mb	133	-	1.7	1.95	-40.0	105.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JWTBSM	64.0	Mb	104	66	1.7	1.95	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JWTBSMG	64.0	Mb	104	66	1.7	1.95	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JWTBSQ	64.0	Mb	104	-	1.7	1.95	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JWTBSQG	64.0	Mb	104	-	1.7	1.95	-40.0	125.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JWUUAQ	64.0	Mb	104	-	1.7	1.95	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JWUUAQG	64.0	Mb	104	-	1.7	1.95	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JWUUIM	64.0	Mb	133	66	1.7	1.95	-40.0	85.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JWUUIMG	64.0	Mb	133	66	1.7	1.95	-40.0	85.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JWUUIQ	64.0	Mb	133	-	1.7	1.95	-40.0	85.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JWUUIQG	64.0	Mb	133	-	1.7	1.95	-40.0	85.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JWUUJQ	64.0	Mb	133	-	1.7	1.95	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JWUUJQG	64.0	Mb	133	-	1.7	1.95	-40.0	105.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JWUUSM	64.0	Mb	104	66	1.7	1.95	-40.0	125.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JWUUSMG	64.0	Mb	104	66	1.7	1.95	-40.0	125.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JWUUSQ	64.0	Mb	104	-	1.7	1.95	-40.0	125.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JWUUSQG	64.0	Mb	104	-	1.7	1.95	-40.0	125.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JWXGAQ	64.0	Mb	104	-	1.7	1.95	-40.0	105.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JWXGAQG	64.0	Mb	104	-	1.7	1.95	-40.0	105.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JWXGIM	64.0	Mb	133	66	1.7	1.95	-40.0	85.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JWXGIMG	64.0	Mb	133	66	1.7	1.95	-40.0	85.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JWXGIQ	64.0	Mb	133	-	1.7	1.95	-40.0	85.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JWXGIQG	64.0	Mb	133	-	1.7	1.95	-40.0	85.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JWXGJQ	64.0	Mb	133	-	1.7	1.95	-40.0	105.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JWXGJQG	64.0	Mb	133	-	1.7	1.95	-40.0	105.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JWXGSM	64.0	Mb	104	66	1.7	1.95	-40.0	105.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JWXGSMG	64.0	Mb	104	66	1.7	1.95	-40.0	105.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JWZEIM	64.0	Mb	133	66	1.7	1.95	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JWZEIMG	64.0	Mb	133	66	1.7	1.95	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JWZEIQ	64.0	Mb	133	-	1.7	1.95	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JWZEIQG	64.0	Mb	133	-	1.7	1.95	-40.0	85.0	SON	8.0	8X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JWZPAQ	64.0	Mb	104	-	1.7	1.95	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JWZPAQG	64.0	Mb	104	-	1.7	1.95	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JWZPIM	64.0	Mb	133	66	1.7	1.95	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JWZPIMG	64.0	Mb	133	66	1.7	1.95	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JWZPIN	64.0	Mb	133	-	1.7	1.95	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		DRV=75%
W25Q64JWZPING	64.0	Mb	133	-	1.7	1.95	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		DRV=75%
W25Q64JWZPIQ	64.0	Mb	133	-	1.7	1.95	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JWZPIQG	64.0	Mb	133	-	1.7	1.95	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JWZPJQ	64.0	Mb	133	-	1.7	1.95	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JWZPJQG	64.0	Mb	133	-	1.7	1.95	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q64JWZPSQ	64.0	Mb	104	-	1.7	1.95	-40.0	125.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64JWZPSQG	64.0	Mb	104	-	1.7	1.95	-40.0	125.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q64PWBYIH	64.0	Mb	166	104	1.65	1.95	-40.0	85.0	WLCSP	12.0			SPI/Dual/Quad	UD	-	No	1bit	-
W25Q64PWBYIHG	64.0	Mb	166	104	1.65	1.95	-40.0	85.0	WLCSP	12.0			SPI/Dual/Quad	UD	-	No	1bit	-
W25Q64PWBYIM	64.0	Mb	166	104	1.65	1.95	-40.0	85.0	WLCSP	12.0			SPI/Dual/Quad	UD	-	No	1bit	-
W25Q64PWBYIMG	64.0	Mb	166	104	1.65	1.95	-40.0	85.0	WLCSP	12.0			SPI/Dual/Quad	UD	-	No	1bit	-
W25Q64PWSNIM	64.0	Mb	166	104	1.65	1.95	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	S	-	No		-
W25Q64PWSNIMG	64.0	Mb	166	104	1.65	1.95	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	S	-	No		-
W25Q64PWSNIQ	64.0	Mb	166	104	1.65	1.95	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	S	-	No		-
W25Q64PWSNIQG	64.0	Mb	166	104	1.65	1.95	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	S	-	No		-
W25Q64PWSSIM	64.0	Mb	166	104	1.65	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	S	-	No		-
W25Q64PWSSIMG	64.0	Mb	166	104	1.65	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	S	-	No		-
W25Q64PWSSIQ	64.0	Mb	166	104	1.65	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	S	-	No		-
W25Q64PWSSIQG	64.0	Mb	166	104	1.65	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	S	-	No		-
W25Q64PWTBIM	64.0	Mb	166	104	1.65	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q64PWTBIMG	64.0	Mb	166	104	1.65	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q64PWTBIQ	64.0	Mb	166	104	1.65	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q64PWTBIQG	64.0	Mb	166	104	1.65	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q64PWUUIM	64.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q64PWUUIMG	64.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q64PWUUIQ	64.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q64PWUUIQG	64.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q64PWXGIM	64.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q64PWXGIMG	64.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q64PWXGIQ	64.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q64PWXGIQG	64.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q64PWXHIM	64.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	UD	-	No		-
W25Q64PWXHIMG	64.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	UD	-	No		-
W25Q64PWXHIQ	64.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	UD	-	No		-
W25Q64PWXHIQG	64.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	UD	-	No		-
W25Q64PWZPIM	64.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q64PWZPIMG	64.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q64PWZPIQ	64.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q64PWZPIQG	64.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q64PYBYIH	64.0	Mb	133	84	1.65	1.95	-40.0	85.0	WLCSP	12.0			SPI/Dual/Quad	UD	-	No	1bit	1.2V I/O
W25Q64PYBYIHG	64.0	Mb	133	84	1.65	1.95	-40.0	85.0	WLCSP	12.0			SPI/Dual/Quad	UD	-	No	1bit	1.2V I/O
W25Q64PYBYIM	64.0	Mb	133	84	1.65	1.95	-40.0	85.0	WLCSP	12.0			SPI/Dual/Quad	UD	-	No	1bit	1.2V I/O
W25Q64PYBYIMG	64.0	Mb	133	84	1.65	1.95	-40.0	85.0	WLCSP	12.0			SPI/Dual/Quad	UD	-	No	1bit	1.2V I/O
W25Q64PYTBIM	64.0	Mb	133	84	1.65	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	UD	-	No		1.2V I/O
W25Q64PYTBIMG	64.0	Mb	133	84	1.65	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	UD	-	No		1.2V I/O
W25Q64PYTBIQ	64.0	Mb	133	84	1.65	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	UD	-	No		1.2V I/O
W25Q64PYTBIQG	64.0	Mb	133	84	1.65	1.95	-40.0	85.0	TFBGA (5X5)	24.0	6X8	MM^2	SPI/Dual/Quad	UD	-	No		1.2V I/O
W25Q64RVCJJM			133	104	2.7	3.6							SPI/Dual/Quad	UD	-	No		-
W25Q64RVCJJMG			133	104	2.7	3.6							SPI/Dual/Quad	UD	-	No		-
W25Q64RVCJJQ			133	-	2.7	3.6							SPI/Dual/Quad	UD	-	No		-
W25Q64RVCJJQG			133	-	2.7	3.6							SPI/Dual/Quad	UD	-	No		-
W25Q64RVCNJM	64.0	Mb	133	104	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	UD	-	No		-
W25Q64RVCNJMG	64.0	Mb	133	104	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	UD	-	No		-
W25Q64RVCNJQ	64.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	UD	-	No		-
W25Q64RVCNJQG	64.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	UD	-	No		-
W25Q64RVCPJM	64.0	Mb	133	104	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	UD	-	No		-
W25Q64RVCPJMG	64.0	Mb	133	104	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	UD	-	No		-
W25Q64RVCPJQ	64.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	UD	-	No		-
W25Q64RVCPJQG	64.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	UD	-	No		-
W25Q64RVCSJM	64.0	Mb	133	104	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	UD	-	No		-
W25Q64RVCSJMG	64.0	Mb	133	104	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	UD	-	No		-
W25Q64RVCSJQ	64.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	UD	-	No		-
W25Q64RVCSJQG	64.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	UD	-	No		-
W25Q64RVXGJM			133	104	2.7	3.6							SPI/Dual/Quad	UD	-	No		-
W25Q64RVXGJMG			133	104	2.7	3.6							SPI/Dual/Quad	UD	-	No		-
W25Q64RVXGJQ	64.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	UD	-	No		-
W25Q64RVXGJQG	64.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	4X4	MM^2	SPI/Dual/Quad	UD	-	No		-
W25Q80DVBYIG	8.0	Mb	104	-	2.7	3.6	-40.0	85.0	WLCSP	8.0			SPI/Dual/Quad	P	-	No		-
W25Q80DVBYIGG	8.0	Mb	104	-	2.7	3.6	-40.0	85.0	WLCSP	8.0			SPI/Dual/Quad	P	-	No		-
W25Q80DVSNIG	8.0	Mb	104	-	2.7	3.6	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q80DVSNIGG	8.0	Mb	104	-	2.7	3.6	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q80DVSNJG	8.0	Mb	104	-	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q80DVSNJGG	8.0	Mb	104	-	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q80DVSSIG	8.0	Mb	104	-	2.7	3.6	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q80DVSSIGG	8.0	Mb	104	-	2.7	3.6	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q80DVUXIE	8.0	Mb	104	-	2.7	3.6	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q80DVUXIEG	8.0	Mb	104	-	2.7	3.6	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q80DVUXJE	8.0	Mb	104	-	2.7	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q80DVUXJEG	8.0	Mb	104	-	2.7	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q80DVZPIG	8.0	Mb	104	-	2.7	3.6	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q80DVZPIGG	8.0	Mb	104	-	2.7	3.6	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q80DVZPJG	8.0	Mb	104	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q80DVZPJGG	8.0	Mb	104	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q80EWUXIE	8.0	Mb	104	-	1.65	1.95	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q80EWUXIEG	8.0	Mb	104	-	1.65	1.95	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q80PWSNIM	8.0	Mb	166	104	1.65	1.95	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	S	-	No		-
W25Q80PWSNIMG	8.0	Mb	166	104	1.65	1.95	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	S	-	No		-
W25Q80PWSNIQ	8.0	Mb	166	-	1.65	1.95	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	S	-	No		-
W25Q80PWSNIQG	8.0	Mb	166	-	1.65	1.95	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual/Quad	S	-	No		-
W25Q80PWSSIM	8.0	Mb	166	104	1.65	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	S	-	No		-
W25Q80PWSSIMG	8.0	Mb	166	104	1.65	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	S	-	No		-
W25Q80PWSSIQ	8.0	Mb	166	-	1.65	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	S	-	No		-
W25Q80PWSSIQG	8.0	Mb	166	-	1.65	1.95	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual/Quad	S	-	No		-
W25Q80PWUUIM	8.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q80PWUUIMG	8.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q80PWUUIQ	8.0	Mb	166	-	1.65	1.95	-40.0	85.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q80PWUUIQG	8.0	Mb	166	-	1.65	1.95	-40.0	85.0	SON	8.0	4X3	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q80PWXHIM	8.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q80PWXHIMG	8.0	Mb	166	104	1.65	1.95	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q80PWXHIQ	8.0	Mb	166	-	1.65	1.95	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q80PWXHIQG	8.0	Mb	166	-	1.65	1.95	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	S	-	No		-
W25Q80RVSNJM	8.0	Mb	133	84	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q80RVSNJMG	8.0	Mb	133	84	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q80RVSNJQ	8.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q80RVSNJQG	8.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	P	-	No		-
W25Q80RVSSJM	8.0	Mb	133	84	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q80RVSSJMG	8.0	Mb	133	84	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q80RVSSJQ	8.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q80RVSSJQG	8.0	Mb	133	-	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	P	-	No		-
W25Q80RVXHJM	8.0	Mb	133	84	2.7	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q80RVXHJMG	8.0	Mb	133	84	2.7	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q80RVXHJQ	8.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q80RVXHJQG	8.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q80RVZPJM	8.0	Mb	133	84	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q80RVZPJMG	8.0	Mb	133	84	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q80RVZPJQ	8.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q80RVZPJQG	8.0	Mb	133	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual/Quad	P	-	No		-
W25Q81DVSNAG	8.0	Mb	80	-	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q81DVSNAGG	8.0	Mb	80	-	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q81DVSNSG	8.0	Mb	80	-	2.7	3.6	-40.0	125.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q81DVSNSGG	8.0	Mb	80	-	2.7	3.6	-40.0	125.0	SOP	8.0	150	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q81DVSSAG	8.0	Mb	80	-	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q81DVSSAGG	8.0	Mb	80	-	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q81DVSSSG	8.0	Mb	80	-	2.7	3.6	-40.0	125.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q81DVSSSGG	8.0	Mb	80	-	2.7	3.6	-40.0	125.0	SOP	8.0	208	MIL	SPI/Dual/Quad	-	P	Yes		-
W25Q81DVXHAG	8.0	Mb	80	-	2.7	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q81DVXHAGG	8.0	Mb	80	-	2.7	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q81DVXHSG	8.0	Mb	80	-	2.7	3.6	-40.0	125.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25Q81DVXHSGG	8.0	Mb	80	-	2.7	3.6	-40.0	125.0	SON	8.0	2X3	MM^2	SPI/Dual/Quad	-	P	Yes		-
W25X05CLSNIG	512.0	Kb	104	-	2.3	3.6	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual	P	-	No		-
W25X05CLSNIGG	512.0	Kb	104	-	2.3	3.6	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual	P	-	No		-
W25X05CLUXIG	512.0	Kb	104	-	2.3	3.6	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual	P	-	No		-
W25X05CLUXIGG	512.0	Kb	104	-	2.3	3.6	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual	P	-	No		-
W25X10CLSNIG	1.0	Mb	104	-	2.3	3.6	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual	P	-	No		-
W25X10CLSNIGG	1.0	Mb	104	-	2.3	3.6	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual	P	-	No		-
W25X10CLUXIG	1.0	Mb	104	-	2.3	3.6	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual	P	-	No		-
W25X10CLUXIGG	1.0	Mb	104	-	2.3	3.6	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual	P	-	No		-
W25X20CLSNIG	2.0	Mb	104	-	2.3	3.6	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual	P	-	No		-
W25X20CLSNIGG	2.0	Mb	104	-	2.3	3.6	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual	P	-	No		-
W25X20CLUXIG	2.0	Mb	104	-	2.3	3.6	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual	P	-	No		-
W25X20CLUXIGG	2.0	Mb	104	-	2.3	3.6	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual	P	-	No		-
W25X20CLZPIG	2.0	Mb	104	-	2.3	3.6	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual	P	-	No		-
W25X20CLZPIGG	2.0	Mb	104	-	2.3	3.6	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual	P	-	No		-
W25X20CVSNAG	2.0	Mb	80	-	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual	-	P	Yes		-
W25X20CVSNAGG	2.0	Mb	80	-	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual	-	P	Yes		-
W25X20CVSNBG	2.0	Mb	80	-	2.7	3.6	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual	-	P	Yes		-
W25X20CVSNBGG	2.0	Mb	80	-	2.7	3.6	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual	-	P	Yes		-
W25X20CVSNSG	2.0	Mb	80	-	2.7	3.6	-40.0	125.0	SOP	8.0	150	MIL	SPI/Dual	-	P	Yes		-
W25X20CVSNSGG	2.0	Mb	80	-	2.7	3.6	-40.0	125.0	SOP	8.0	150	MIL	SPI/Dual	-	P	Yes		-
W25X40CLSNIG	4.0	Mb	104	-	2.3	3.6	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual	P	-	No		-
W25X40CLSNIGG	4.0	Mb	104	-	2.3	3.6	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual	P	-	No		-
W25X40CLSSIG	4.0	Mb	104	-	2.3	3.6	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual	P	-	No		-
W25X40CLSSIGG	4.0	Mb	104	-	2.3	3.6	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual	P	-	No		-
W25X40CLUXIG	4.0	Mb	104	-	2.3	3.6	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual	P	-	No		-
W25X40CLUXIGG	4.0	Mb	104	-	2.3	3.6	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual	P	-	No		-
W25X40CLZPIG	4.0	Mb	104	-	2.3	3.6	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual	P	-	No		-
W25X40CLZPIGG	4.0	Mb	104	-	2.3	3.6	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual	P	-	No		-
W25X40CVSNAG	4.0	Mb	80	-	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual	-	P	Yes		-
W25X40CVSNAGG	4.0	Mb	80	-	2.7	3.6	-40.0	105.0	SOP	8.0	150	MIL	SPI/Dual	-	P	Yes		-
W25X40CVSNBG	4.0	Mb	80	-	2.7	3.6	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual	-	P	Yes		-
W25X40CVSNBGG	4.0	Mb	80	-	2.7	3.6	-40.0	85.0	SOP	8.0	150	MIL	SPI/Dual	-	P	Yes		-
W25X40CVSNSG	4.0	Mb	80	-	2.7	3.6	-40.0	125.0	SOP	8.0	150	MIL	SPI/Dual	-	P	Yes		-
W25X40CVSNSGG	4.0	Mb	80	-	2.7	3.6	-40.0	125.0	SOP	8.0	150	MIL	SPI/Dual	-	P	Yes		-
W25X40CVSSAG	4.0	Mb	80	-	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual	-	P	Yes		-
W25X40CVSSAGG	4.0	Mb	80	-	2.7	3.6	-40.0	105.0	SOP	8.0	208	MIL	SPI/Dual	-	P	Yes		-
W25X40CVSSBG	4.0	Mb	80	-	2.7	3.6	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual	-	P	Yes		-
W25X40CVSSBGG	4.0	Mb	80	-	2.7	3.6	-40.0	85.0	SOP	8.0	208	MIL	SPI/Dual	-	P	Yes		-
W25X40CVSSSG	4.0	Mb	80	-	2.7	3.6	-40.0	125.0	SOP	8.0	208	MIL	SPI/Dual	-	P	Yes		-
W25X40CVSSSGG	4.0	Mb	80	-	2.7	3.6	-40.0	125.0	SOP	8.0	208	MIL	SPI/Dual	-	P	Yes		-
W25X40CVUXAG	4.0	Mb	80	-	2.7	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual	-	P	Yes		-
W25X40CVUXAGG	4.0	Mb	80	-	2.7	3.6	-40.0	105.0	SON	8.0	2X3	MM^2	SPI/Dual	-	P	Yes		-
W25X40CVUXBG	4.0	Mb	80	-	2.7	3.6	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual	-	P	Yes		-
W25X40CVUXBGG	4.0	Mb	80	-	2.7	3.6	-40.0	85.0	SON	8.0	2X3	MM^2	SPI/Dual	-	P	Yes		-
W25X40CVZPAG	4.0	Mb	80	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual	-	P	Yes		-
W25X40CVZPAGG	4.0	Mb	80	-	2.7	3.6	-40.0	105.0	SON	8.0	5X6	MM^2	SPI/Dual	-	P	Yes		-
W25X40CVZPBG	4.0	Mb	80	-	2.7	3.6	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual	-	P	Yes		-
W25X40CVZPBGG	4.0	Mb	80	-	2.7	3.6	-40.0	85.0	SON	8.0	5X6	MM^2	SPI/Dual	-	P	Yes		-
W25X40CVZPSG	4.0	Mb	80	-	2.7	3.6	-40.0	125.0	SON	8.0	5X6	MM^2	SPI/Dual	-	P	Yes		-
W25X40CVZPSGG	4.0	Mb	80	-	2.7	3.6	-40.0	125.0	SON	8.0	5X6	MM^2	SPI/Dual	-	P	Yes		-

Online Purchasing Guide.csv

Posts on KnightLi Blog

PersonaPlex Quick Guide: Full-Duplex Conversational Speech with Persona and Voice Control

What It Is Good For

Prerequisites

Installation and Environment

Launch Live Server

Offline Evaluation

Built-in Voice Labels

Prompting Tips

Summary

Anthropic's Harness Direction: Agent Infrastructure Is Becoming an Agent OS

Core Judgment

Why This Matters

Anthropic’s Approach: From Concrete Harness to Meta-Harness

1) Session Is Not the Context Window

2) Harness as a Replaceable Orchestration Layer

3) Sandbox Is the “Hands,” Not the “Brain”

Performance and Security Insights

Related Links

OpenClaw and Agent Harness: Why It Looks Like AGI

Core Conclusion

What Is a Harness

Why OpenClaw Feels Different

Value and Boundaries

Sharing an Agent Skill for E-commerce Product Image Cutout and Standardization

What this skill solves

When to use it

Quick start

Output rules

Main parameters

Workflow

How it differs from a basic cutout script

SKILL.md source

scripts/run_pipeline.py source

How to Use Google Nano Banana for Image Cutouts

What this code does

Before you run it

How to get GEMINI_API_KEY

Example directory structure

How to run it

Core API call flow

Why local post-processing is still needed

Full source code

Good places to improve it further

Summary

What are Ollama cloud models and how do you use them

What are Ollama cloud models

How they differ from local models

How to identify a cloud model

How to use them

Summary

Windows Task Manager data stops updating: the refresh speed is usually set to Paused

Symptoms

Cause

Fix

Additional notes

How to Download a GGUF Model from Hugging Face and Import It into Ollama

Step 1: Download the GGUF file from Hugging Face

Step 2: Write the Modelfile

Step 3: Import it into Ollama

Step 4: Run the model

How to inspect an existing model’s Modelfile

When this approach makes sense

Common notes

Conclusion

How to Troubleshoot Slow `ollama pull` Model Downloads

Get the model file download URLs

Manifest URL

Blob URLs

The real download URL after the redirect

Adjust your network settings

Before-and-after comparison

A more practical troubleshooting order

Conclusion

Anthropic and OpenClaw Timeline: The Full Sequence of Events

Background

Timeline (January to April 2026)

January 2026

February 2026

March 2026

Alternative: `git-commit-push-zh`

Appendix: Original `SKILL.md`

How to Read the `PROCESSOR` Column