1M Token Context
Accepts up to 1 million tokens in a single request (beta), enabling reasoning across entire codebases, lengthy contracts, or dozens of documents at once.
Claude Sonnet 4.6 is a text generation model developed by Anthropic, released in February 2026 as an upgrade to the Sonnet line of mid-tier models. It features a 1 million token context window in beta, allowing it to process entire codebases, lengthy legal documents, or large collections of research papers within a single request. The model is designed for coding, agentic workflows, computer use, and professional knowledge work at scale. Sonnet 4.6 is particularly suited for developers and enterprises running high-volume workloads that require consistent instruction following, accurate tool selection, and reliable error correction across long sessions. It includes improved computer use capabilities, enabling it to navigate browsers, fill multi-step web forms, and automate desktop workflows. Anthropic's safety evaluations found it to be as safe as or safer than other recent Claude models, with noted resistance to prompt injection attacks.
High-signal model metadata in a structured two-column overview table.
The entity that provides this model.
The routed model identifier exposed by upstream providers.
The number of tokens supported by the input context window.
The number of tokens that can be generated by the model in a single request.
Whether the model's code is available for public use.
When the model was first released.
When the model's knowledge was last updated.
The providers that offer this model. This is not an exhaustive list.
Types of data this model can process.
A fuller summary of positioning, capabilities, and source-specific details for Claude 4.6 Sonnet.
Claude Sonnet 4.6 is a text generation model developed by Anthropic, released in February 2026 as an upgrade to the Sonnet line of mid-tier models. It features a 1 million token context window in beta, allowing it to process entire codebases, lengthy legal documents, or large collections of research papers within a single request. The model is designed for coding, agentic workflows, computer use, and professional knowledge work at scale.
Sonnet 4.6 is particularly suited for developers and enterprises running high-volume workloads that require consistent instruction following, accurate tool selection, and reliable error correction across long sessions. It includes improved computer use capabilities, enabling it to navigate browsers, fill multi-step web forms, and automate desktop workflows. Anthropic's safety evaluations found it to be as safe as or safer than other recent Claude models, with noted resistance to prompt injection attacks.
Accepts up to 1 million tokens in a single request (beta), enabling reasoning across entire codebases, lengthy contracts, or dozens of documents at once.
Supports the full software development lifecycle including planning, implementation, debugging, and large-scale refactors across multiple files.
Handles long-running, multi-step autonomous tasks with improved instruction following, tool selection, and error correction over extended sessions.
Controls browsers and desktop software to navigate complex spreadsheets, fill multi-step web forms, and automate workflows that previously required human intervention.
Supports structured tool calling, allowing the model to invoke external functions and APIs as part of a reasoning or task-completion workflow.
Compatible with Model Context Protocol (MCP) servers, enabling connection to external data sources and services through a standardized interface.
Applies multi-step reasoning to complex professional tasks including financial analysis, research synthesis, and frontend code generation.
Includes Anthropic's safety evaluations with documented resistance to prompt injection attacks, rated as safe as or safer than other recent Claude models.
Primary API pricing shown in the same “quick compare” spirit as the reference page.
Additional usage-cost dimensions synced into the project for this model.
Places where this model is available, based on the synced detail-page metadata.
Endpoint-level provider data currently available for this model.
The configurable options currently documented for this model.
When enabled, the model will explain its thought process step-by-step before providing a final answer. This can help users understand how the model arrived at its conclusions, but may result in longer responses. The model dynamically decides when and how much to think.
Parameters currently listed by OpenRouter or the local catalog for this model.
Benchmark scores synced from the current model source and normalized into the local catalog.
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ARC-AGI-2
Novel abstract reasoning and pattern recognition
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Finance Agent
Financial analysis and decision-making tasks
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GPQA Diamond
PhD-level science questions (biology, physics, chemistry)
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HLE
Questions that challenge frontier models across many domains
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IFBench
Instruction following accuracy
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Long Context Reasoning
Reasoning across long documents and contexts
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MATH-500
Undergraduate and competition-level math problems
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MCP-Atlas Tool Use
Structured tool use via Model Context Protocol
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MMLU-Pro
Expert knowledge across 14 academic disciplines
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MMMB
Multilingual and multimodal understanding
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OSWorld-Verified
Autonomous computer use and desktop tasks
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SciCode
Scientific research coding and numerical methods
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SWE-bench Verified
Real GitHub issues requiring multi-file code fixes
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Terminal-Bench 2.0
Agentic coding and terminal command tasks
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TerminalBench Hard
Agentic coding and terminal command tasks
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τ²-Bench
Agentic tool use in realistic scenarios
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τ²-bench Retail
Agentic tool use in retail scenarios
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τ²-bench Telecom
Agentic tool use in telecom scenarios
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Official model cards, release notes, docs, and other references synced from the source page.
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Compare pricing, benchmarks, strengths, and best use cases.
Compare pricing, benchmarks, strengths, and best use cases.
Recent daily stories tied to Claude 4.6 Sonnet through direct model mentions or provider-level coverage.
Anthropic and OpenAI move deeper into real workflows.
Anthropic and Hugging Face move deeper into real workflows.
NVIDIA and Hugging Face move deeper into real workflows.
Anthropic and Qwen move deeper into real workflows.
Claude 4.6 Sonnet discussions are most active in r/SillyTavernAI, r/DeepSeek. Top Reddit threads cluster around coding workflow discussions. The strongest match in this snapshot has 113 upvotes and 40 comments.
[https://openrouter.ai/anthropic/claude-sonnet-4.6](https://openrouter.ai/anthropic/claude-sonnet-4.6)
Same price as Sonnet 4.5
Honestly, it isn't a terrible model.
I would put it on par with maybe Claude 4.6 sonnet.
For creativity, as I usually need that for writing. Its pretty excellent. Just not the feeling of a model like opus would.
I don't really use any other model except Kimi K2.6, as that's the best one so far.
For coding, it's pretty good too, though I've only done some html stuff with it.
And the fact it's in preview, just only means there's a hole lot more this model can do! Once it gets better at roleplay (still a bit generic, better than deepseek V3.2 in some way imo). It would be my daily driver most definitely.
Claude Sonnet 4.6 supports a 1 million token context window, currently available in beta. This allows it to process large inputs such as entire codebases or lengthy document collections in a single request.
Based on the metadata provided, the training date for Claude Sonnet 4.6 is February 2026.
Claude Sonnet 4.6 is designed for coding, agentic workflows, computer use, and enterprise knowledge work. It is particularly well-suited for high-volume deployments requiring consistent instruction following and long-session reliability.
Yes. Claude Sonnet 4.6 supports structured tool calling and is compatible with Model Context Protocol (MCP) servers, making it suitable for integration with external APIs and data sources.
Anthropic's safety evaluations found Claude Sonnet 4.6 to be as safe as or safer than other recent Claude models. It has documented resistance to prompt injection attacks, which is relevant for agentic and computer use deployments.
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