AI Models on KnightLi Blog

Claude Opus 4.7, Sonnet 4.6, and Haiku 4.5: Differences and Model Selection Guide

Fri, 08 May 2026 08:19:03 +0800

Anthropic’s core large language models mainly evolve through the Claude series. As of May 2026, Claude’s mainstream product line has entered the 4.x stage, while still following a three-tier structure: Opus is for maximum capability, Sonnet balances performance and cost, and Haiku focuses on speed and cost effectiveness.

If you only want a quick rule of thumb, remember this:

For the most complex and demanding reasoning and agentic coding: start with Claude Opus 4.7.
For most development, writing, analysis, and enterprise API scenarios: Claude Sonnet 4.6 is the safest starting point.
For high-concurrency, low-latency, cost-sensitive tasks: consider Claude Haiku 4.5.

Current Mainstream Models

According to Anthropic’s official model documentation, the current Claude mainstream models can be understood this way.

Model	Positioning	Suitable Scenarios
`Claude Opus 4.7`	The strongest generally available model, built for complex reasoning and agentic coding	Large codebase refactoring, multi-step tasks, complex strategy analysis, work that requires stronger consistency
`Claude Sonnet 4.6`	The balance point between speed, capability, and cost, with a 1 million token context window	Code generation, long-document analysis, enterprise knowledge work, Agent development, everyday high-quality production tasks
`Claude Haiku 4.5`	The fastest and lower-cost small-model tier, while still retaining capabilities close to frontier models	Real-time chat, customer support, batch classification, simple code collaboration, high-concurrency API calls

There are two naming details worth noting.

First, the official name is Claude Haiku 4.5, not Claude 4.5 Haiku. Second, Claude Mythos Preview is not a mainstream available model for regular users or developers. It is a controlled research preview related to Project Glasswing, mainly aimed at defensive cybersecurity workflows, and should not be mixed into regular Claude model selection.

Opus: For the Hardest Problems

Opus is the tier Anthropic uses for its strongest models. The point of Claude Opus 4.7 is not being cheap or the fastest option, but being better suited to complex, multi-step tasks that require repeated verification.

It is better suited to these situations:

Large code changes across many files.
Complex system refactoring and architectural reasoning.
Long-chain Agent tasks.
Work requiring stronger visual understanding, document understanding, and multi-turn planning.
Enterprise analysis tasks where mistakes are costly.

If the cost of a single failed task is high, or you want the model to spend more time understanding context before acting, Opus is usually more worth trying.

Sonnet: The Default Starting Point for Most People

Claude Sonnet 4.6 is better suited as the default entry point. Its positioning is not “a lower-end Opus,” but rather a way to put sufficiently strong reasoning, coding, visual understanding, long context, and agent planning into a more controllable cost and speed profile.

For developers, the value of Sonnet 4.6 mainly comes from three points:

It can handle very long context, making it suitable for codebases, contracts, reports, or multiple documents.
It is easier to use as a regular model in Claude Code, API, and enterprise scenarios.
It costs less than Opus, making it more suitable for high-frequency use.

If you do not know which Claude model to start with, Claude Sonnet 4.6 is usually the right beginning. Switch to Opus only when the task clearly needs stronger capability.

Haiku: When Fast and Affordable Matter More

Claude Haiku 4.5 is the small-model tier, but it should not simply be understood as a “weak model.” Anthropic positions it as fast and low cost while retaining capabilities close to frontier models.

It fits these scenarios:

Real-time chat and customer support bots.
Large-scale short-text classification.
Low-latency API calls.
Simple code edits and rapid prototypes.
Subtask execution in multi-Agent workflows.

If the task itself is clear, the context is not complex, and throughput matters, Haiku is often more reasonable than blindly using a larger model.

Claude’s Tool Capabilities

The Claude series is not just a set of chat models. Anthropic now places model capabilities inside multiple products and developer tools.

Claude Code is a command-line coding tool for developers. It can read codebases, edit files, run commands, and execute tests, making it suitable for sustained engineering work. Its experience depends heavily on the model’s code understanding, context management, and tool-calling stability.

Computer Use lets the model operate a desktop environment through screenshots, mouse actions, and keyboard input. It still needs to be used carefully, and the official documentation emphasizes running it in an isolated environment to avoid mistakes or security risks.

Artifacts is more of a Claude app-side experience. It can place code, page prototypes, charts, or document outputs into the interface for preview and iteration. It is not a standalone model, but part of the Claude product experience.

As for terms like “Managed Agents” or “self-evolving Agents,” be careful when writing about them. Anthropic is indeed strengthening Agent SDK, Claude Code, long context, tool use, and enterprise workflows, but it should not be described as already having uncontrolled self-evolution capability.

Access Options

Regular users can use Claude through the Claude.ai web app or mobile apps. Different plans affect available models, usage limits, and features.

Developers usually have several access options:

Anthropic Console and Claude API.
Amazon Bedrock.
Google Cloud Vertex AI.
Microsoft Foundry.

Specific available models, context windows, pricing, and regional support can change. Before development, it is best to rely on Anthropic’s official model documentation and the relevant cloud platform pages.

How to Choose

In actual use, you do not need to chase the strongest model from the beginning. A better approach is to tier model choice by task cost.

For everyday writing, code generation, long-document analysis, knowledge organization, and most Agent prototypes, start with Claude Sonnet 4.6. It is usually the best starting point for cost effectiveness and general capability.

If the task requires stronger complex reasoning, cross-file engineering changes, long-chain planning, or higher reliability, switch to Claude Opus 4.7.

If the task is simple, high-volume, and latency-sensitive, such as classification, summarization, customer support, or batch processing, put Claude Haiku 4.5 on the shortlist.

Claude’s model line is not simply “new versions replacing old versions.” It is a toolbox layered by task difficulty, speed, and cost. Choosing the right model matters more than blindly using the most expensive one.

References

Anthropic Models Overview: https://platform.claude.com/docs/en/about-claude/models/overview
Introducing Claude Opus 4.7: https://www.anthropic.com/news/claude-opus-4-7
Introducing Claude Sonnet 4.6: https://www.anthropic.com/news/claude-sonnet-4-6
Introducing Claude Haiku 4.5: https://www.anthropic.com/news/claude-haiku-4-5
Anthropic Computer Use Tool: https://docs.anthropic.com/en/docs/build-with-claude/computer-use

What Is the Difference Between GPT-5.5, GPT-5.5 Instant, GPT-5.5 Thinking, and GPT-5.5 Pro?

Thu, 07 May 2026 21:59:33 +0800

OpenAI now separates GPT-5.5 into clearer usage tiers: Instant, Thinking, and Pro.

Many people mix up GPT-5.5, GPT-5.5 Instant, GPT-5.5 Thinking, and GPT-5.5 Pro. The short version: GPT-5.5 is the overall name for this generation of model capabilities. Instant is the fast everyday model, Thinking is the deeper reasoning mode, and Pro is a heavier research-grade mode.

Quick Comparison

Name	What It Is	Best For	Speed/Cost	Availability
GPT-5.5	Main GPT-5.5 model/family name; in ChatGPT it usually maps to the capability positioning of GPT-5.5 Thinking	Complex work, code, research, analysis, tool use	Heavier than Instant, but more capable	Plus, Pro, Business, Enterprise
GPT-5.5 Instant	Fast default model, replacing GPT-5.3 Instant	Daily Q&A, writing, summarization, light coding, quick lookup	Fastest and most quota-efficient	Gradual rollout to all ChatGPT users
GPT-5.5 Thinking	Deep reasoning mode	Hard problems, long-context analysis, complex code, research, document-heavy tasks	Slower, but more reliable reasoning	Paid users can select it manually
GPT-5.5 Pro	Heavier research-grade mode	High-risk or high-precision tasks: law, business, education, data science, scientific analysis	Slowest and heaviest, optimized for quality	Pro, Business, Enterprise, Edu

If you only want one rule:

Fast everyday tasks: use GPT-5.5 Instant.
Complex reasoning and code analysis: use GPT-5.5 Thinking.
Especially hard, important, or accuracy-sensitive work: use GPT-5.5 Pro.

What Is GPT-5.5

When people say GPT-5.5 by itself, they usually mean the overall capability of the GPT-5.5 generation, not a single fixed button.

OpenAI positions GPT-5.5 as a stronger model for real work. Its improvements focus on:

agentic coding;
complex code debugging;
research and synthesis;
generating documents, spreadsheets, and presentations;
computer use and cross-tool work;
sustained reasoning and self-checking in long tasks.

In ChatGPT, users do not usually see a vague GPT-5.5 button. They see more specific options: Instant, Thinking, and Pro. So if someone says “I am using GPT-5.5,” it is worth asking: Instant, Thinking, or Pro?

GPT-5.5 Instant: Default, Fast, Everyday Use

GPT-5.5 Instant is the new fast default model. OpenAI’s official announcement says it begins replacing GPT-5.3 Instant as the default ChatGPT model and is available in the API as chat-latest.

It is suitable for:

everyday chat;
quick Q&A;
ordinary writing;
article summarization;
email rewriting;
light code explanation;
simple tables and lists;
tasks that do not need long reasoning.

Instant’s main advantages are speed and default availability. You do not need to manually select a reasoning mode every time, and ordinary questions do not pay a higher latency cost.

It also changes the default tone: OpenAI emphasizes that GPT-5.5 Instant answers more clearly and concisely, with stronger personalization. For ordinary users, that makes it better as the model you leave open all day.

The caveat is that Instant is not the strongest mode. For complex math, long code, architecture design, multi-file analysis, or serious research, it may switch to Thinking automatically, or you may need to select Thinking manually.

GPT-5.5 Thinking: The Main Mode for Complex Tasks

GPT-5.5 Thinking is the reasoning mode better suited to complex tasks.

It fits:

code debugging;
architecture design;
multi-step reasoning;
long-document analysis;
academic material organization;
business scenario planning;
data-analysis explanation;
tasks that require comparison, tradeoffs, and verification.

Thinking spends more time reasoning. The OpenAI Help Center says that when GPT-5.5 Thinking or GPT-5.5 Pro starts reasoning, it may first show a short preamble explaining what it plans to do. Users can also add instructions while the model is still thinking to adjust direction early.

In ChatGPT, when manually choosing Thinking, users can also adjust thinking time. According to the official explanation, Plus and Business users can use Standard and Extended; Pro users also have options such as Light and Heavy.

My interpretation: Thinking is the default choice for serious work. Whenever a task involves multiple steps, long context, or higher accuracy requirements, it is more suitable than Instant.

GPT-5.5 Pro: Research-Grade, Heavier, More Rigorous

GPT-5.5 Pro is the mode for harder problems and higher-precision work.

It fits:

legal material analysis;
business research;
education and curriculum design;
data science;
scientific literature synthesis;
deep review before high-risk decisions;
multi-document, multi-constraint, multi-round verification tasks.

In the GPT-5.5 announcement, OpenAI says early testers found GPT-5.5 Pro to improve over GPT-5.4 Pro in completeness, structure, accuracy, relevance, and usefulness, especially in business, law, education, and data science.

The downside is also clear: Pro is slower and heavier, and it is not meant for every small question. It is more like an expert reviewer or research partner than a daily chat entry point.

Pro also has special tool-support limitations. The OpenAI Help Center says Apps, Memory, Canvas, and image generation are not available in Pro. If your task needs those ChatGPT features, Instant or Thinking may be the better choice.

Tool Support Differences

According to the OpenAI Help Center, GPT-5.5 Instant and GPT-5.5 Thinking support common ChatGPT tools, including:

Web search;
Data analysis;
Image analysis;
File analysis;
Canvas;
Image generation;
Memory;
Custom Instructions.

GPT-5.5 Pro is more focused on research-grade reasoning, but not all ChatGPT tools are available. Pay particular attention:

Apps are unavailable;
Memory is unavailable;
Canvas is unavailable;
image generation is unavailable.

So when choosing a model, do not only ask “which one is smarter.” Also ask which tools you need.

Context Window Differences

The OpenAI Help Center describes ChatGPT context windows roughly as:

Mode	Context Window
GPT-5.5 Instant	Free: 16K; Plus/Business: 32K; Pro/Enterprise: 128K
GPT-5.5 Thinking	Usually 256K when manually selected on paid plans; up to 400K on Pro

This means:

Instant is enough for ordinary chat and short documents;
Thinking is better for multi-file work, multi-round research, and long-codebase analysis;
for especially long, complex, high-precision tasks, Pro users can use a larger context and heavier reasoning.

How to Choose

Everyday Q&A

Use GPT-5.5 Instant.

It is fast, smart enough, and good for quick questions, quick writing, and quick edits.

Writing, Summarizing, Email Editing

Start with GPT-5.5 Instant.

If the article is long, needs structural rewriting, or requires multiple rounds of proofreading, switch to GPT-5.5 Thinking.

Coding and Debugging

Use Instant for simple code explanation.

Use Thinking for multi-file debugging, architecture design, and complex error analysis. For very difficult long-running engineering problems, consider Pro.

Research and Material Analysis

Use Thinking for ordinary material organization.

For law, business, scientific research, and data science tasks that need higher precision, Pro is more suitable.

Tasks Requiring Image Generation, Canvas, or Memory

Prefer Instant or Thinking.

Do not automatically choose Pro, because Pro does not support some ChatGPT tools.

Short Conclusion

GPT-5.5 Instant is the everyday default model: fast, clear, quota-efficient, and suitable for most ordinary tasks.

GPT-5.5 Thinking is the main mode for complex work: code, research, long documents, analysis, and multi-step reasoning.

GPT-5.5 Pro is the high-precision research mode: suitable for harder and more important tasks that need more rigor, but with more limits on speed and tool support.

GPT-5.5 itself is more like the overall name for this generation. In practice, the real choice is whether you select Instant, Thinking, or Pro in ChatGPT.

GPT-5.5 Instant announcement: https://openai.com/index/gpt-5-5-instant/
GPT-5.5 announcement: https://openai.com/index/introducing-gpt-5-5/
GPT-5.5 in ChatGPT Help Center: https://help.openai.com/en/articles/11909943-gpt-53-and-gpt-55-in-chatgpt

GPT-5.5 Instant launches: ChatGPT's default model gets more accurate, shorter, and more personal

Thu, 07 May 2026 14:28:40 +0800

OpenAI released GPT-5.5 Instant on May 5, 2026 and began rolling it out as the default model for all ChatGPT users.

The keywords in this update are not “bigger” or “flashier.” They are closer to everyday use: more accurate answers, clearer and shorter responses, a more natural tone, and better use of context users have already shared. For ChatGPT, changes to the default model matter especially because they affect the experience most people actually use every day.

Why the default model matters

Instant is ChatGPT’s daily driver model. Many users do not manually switch models or study the differences between them. Their experience of ChatGPT is the quality of the default model.

So GPT-5.5 Instant is not just another model name. It moves the base experience forward. OpenAI says the update makes everyday interactions more useful and smoother: stronger answers across topics, tighter conversations, and better use of existing context when appropriate.

This kind of improvement is less dramatic than a large multimodal launch, but for hundreds of millions of users, a default model that makes fewer mistakes, writes less unnecessarily, and asks fewer pointless follow-up questions is a major product change.

Fewer hallucinations and more reliable answers

OpenAI puts accuracy first.

In internal evaluations, OpenAI says GPT-5.5 Instant produced 52.5% fewer hallucinated claims than GPT-5.3 Instant on high-stakes prompts covering medicine, law, and finance. On especially difficult conversations users had flagged for factual errors, inaccurate claims were reduced by 37.3%.

These numbers matter. They show OpenAI is not only trying to make the model more fluent, but also continuing to reduce factual errors. In areas such as medicine, law, and finance, a model cannot merely sound smooth. It has to be more cautious and invent less.

This does not mean users should treat ChatGPT as a replacement for professional advice. A more accurate model still needs verification, sources, and human judgment in high-risk contexts. But as a product experience, better factual reliability in the default model reduces many everyday risks.

Stronger everyday task performance

GPT-5.5 Instant also improves across daily tasks.

OpenAI mentions better analysis of photo and image uploads, stronger STEM answers, and better judgment about when to use web search. The last point is important. Many users do not care whether the model internally calls a tool. They care whether the answer is fresh, accurate, and clearly explained.

If the model can better decide which questions need web search and which can be answered directly, users do not have to keep saying “look it up.” ChatGPT feels more like a proactive assistant than a chat box waiting for explicit instructions.

OpenAI’s math example also points in this direction. GPT-5.5 Instant initially accepts an incorrect solution, but then checks the result, finds the algebra error, and solves the corrected equation. The important point is not that it never makes a mistake, but that it has a better chance of catching and repairing one during the reasoning process.

Shorter answers, not less substance

OpenAI also emphasizes that GPT-5.5 Instant gives tighter, more direct answers while keeping useful content and ChatGPT’s friendly tone.

This matters for a default model. AI response fatigue often comes not from too little information, but from too much structure, too much setup, and too much formatting. A simple question can become five headings and a dozen caveats, which feels unnatural.

GPT-5.5 Instant aims to reduce unnecessary verbosity and overformatting, ask fewer unneeded follow-up questions, and avoid decorative clutter. For daily office work, writing advice, life questions, and quick explanations, these changes often matter more than one benchmark score.

Shorter does not mean shallower. A good default model should judge whether the user needs one practical sentence, an explanation, or a full plan. GPT-5.5 Instant is moving toward steadier judgment on that balance.

Personalization keeps improving

Another main thread is personalization.

OpenAI says Instant is now better at using context from past chats, files, and connected Gmail, when available, to make responses more relevant. It decides when extra personalization can improve an answer and searches past conversations faster, so users do not need to repeat background as often.

This is valuable for long-term ChatGPT users. When planning, writing, selecting tools, organizing projects, or continuing a workflow, users may already have provided preferences, constraints, and context in earlier chats. If the model can pick up naturally, it reduces repeated explanation.

But personalization has to come with transparency and control. Otherwise users do not know why the model suddenly references a preference or which memories are shaping an answer.

Memory sources make personalization more visible

OpenAI is also introducing memory sources across all ChatGPT models.

The feature lets users see which context was used to personalize a response, such as saved memories or past chats. If something is outdated, inaccurate, or no longer wanted, users can delete or correct it.

OpenAI also says memory sources are not shown to others when users share a chat. Users can delete chats they do not want cited, edit saved memories in settings, or use temporary chats that do not use or update memory.

This matters. The more personalized an AI assistant becomes, the more it needs to explain “what I used to answer you.” Memory sources may not show every factor, but they move part of personalization out of the black box.

Availability

GPT-5.5 Instant is rolling out from the announcement day to all ChatGPT users, replacing GPT-5.3 Instant as the default model. In the API, it corresponds to chat-latest.

Paid users can continue using GPT-5.3 Instant for three months through model configuration settings before it is retired.

Enhanced personalization from past chats, files, and connected Gmail is rolling out first to Plus and Pro users on the web, with mobile support coming later. OpenAI plans to expand it to Free, Go, Business, and Enterprise in the following weeks. Memory sources are rolling out on the web for ChatGPT consumer plans and will come to mobile later. Availability of specific personalization sources may vary by region.

Short Take

GPT-5.5 Instant is an upgrade to the default ChatGPT experience.

It is not only about stronger model capability. It adjusts accuracy, answer density, tone, context use, and personalization transparency together. For ordinary users, the most direct change should be: less fluff, fewer factual errors, and better continuity with your background.

For OpenAI, this is another step in the evolution of the default assistant. ChatGPT is becoming less of a tool that starts from zero every time and more of a long-term assistant that can remember preferences, understand context, know when to search, and let users manage those memory sources.

AI Models on KnightLi Blog

Claude Opus 4.7, Sonnet 4.6, and Haiku 4.5: Differences and Model Selection Guide

Current Mainstream Models

Opus: For the Hardest Problems

Sonnet: The Default Starting Point for Most People

Haiku: When Fast and Affordable Matter More

Claude’s Tool Capabilities

Access Options

How to Choose

References

What Is the Difference Between GPT-5.5, GPT-5.5 Instant, GPT-5.5 Thinking, and GPT-5.5 Pro?

Quick Comparison

What Is GPT-5.5

GPT-5.5 Instant: Default, Fast, Everyday Use

GPT-5.5 Thinking: The Main Mode for Complex Tasks

GPT-5.5 Pro: Research-Grade, Heavier, More Rigorous

Tool Support Differences

Context Window Differences

How to Choose

Everyday Q&A

Writing, Summarizing, Email Editing

Coding and Debugging

Research and Material Analysis

Tasks Requiring Image Generation, Canvas, or Memory

Short Conclusion

Related Links

GPT-5.5 Instant launches: ChatGPT's default model gets more accurate, shorter, and more personal

Why the default model matters

Fewer hallucinations and more reliable answers

Stronger everyday task performance

Shorter answers, not less substance

Personalization keeps improving

Memory sources make personalization more visible

Availability

Short Take

Links