Claude 4.6 Opus
Anthropic's most intelligent model, setting new standards in agentic coding, complex reasoning, and professional knowledge work.
Anthropic Anthropic's most capable model for complex reasoning
Claude Opus 4.6 is Anthropic's most capable text generation model, released on February 5, 2026. It is designed for long-horizon agentic tasks, complex reasoning, and professional knowledge work across domains such as software development, finance, and legal analysis. A defining feature of this release is its 1 million token context window, available in beta, which allows the model to process and reason over very large volumes of information within a single session. It also introduces adaptive thinking, which automatically calibrates the depth of reasoning applied based on the complexity of the task at hand.
Opus 4.6 is built to handle demanding, real-world workloads with minimal human oversight. It can orchestrate teams of subagents, parallelize work across tools, and sustain long-running tasks across the full software development lifecycle from architecture through deployment. The model supports tool use and MCP server integration, making it suitable for enterprise workflows and autonomous agent pipelines. It is best suited for senior engineers, analysts, and organizations that need to delegate complex, multi-step challenges to an AI system.
What Claude 4.6 Opus supports
Large Context Window
Processes up to 1 million tokens in a single session (currently in beta), enabling analysis of entire codebases, lengthy documents, or large data sets without truncation.
Adaptive Thinking
Automatically adjusts the amount of reasoning effort applied based on task complexity, allocating deeper computation to harder problems and less to simpler ones.
Agentic Coding
Handles long-horizon software development tasks including architecture, implementation, and deployment, with benchmark results on Terminal-Bench 2.0 cited in the model overview.
Tool Use
Accepts tool definitions at inference time and can call external functions or APIs, enabling integration with custom workflows and automated pipelines.
MCP Server Support
Connects to Model Context Protocol servers, allowing the model to interact with external data sources and services through a standardized interface.
Complex Reasoning
Applies multi-step reasoning across rigorous multidisciplinary tasks, with performance on Humanity's Last Exam cited as a benchmark reference in the model overview.
Agentic Web Search
Performs deep, multi-step web research to locate hard-to-find information, with BrowseComp cited as a benchmark for this capability in the model overview.
Professional Knowledge Work
Handles economically valuable tasks in domains such as finance and legal analysis, with GDPval-AA cited as a benchmark evaluation in the model overview.
Subagent Orchestration
Can coordinate and manage teams of subagents, parallelizing work across tools to complete complex, multi-stage tasks with minimal human intervention.
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Get Started FreeBenchmark scores
Scores represent accuracy — the percentage of questions answered correctly on each test.
| Benchmark | What it tests | Standard | Extended Thinking |
|---|---|---|---|
| GPQA Diamond | PhD-level science questions (biology, physics, chemistry) | 84.0% | — |
| HLE | Questions that challenge frontier models across many domains | 18.6% | — |
| SciCode | Scientific research coding and numerical methods | 45.7% | — |
| SWE-bench Verified | Real GitHub issues requiring multi-file code fixes | 80.8% | — |
| Terminal-Bench 2.0 | Agentic coding and terminal command tasks | 65.4% | — |
| ARC-AGI-2 | Novel abstract reasoning and pattern recognition | 68.8% | — |
| BigLaw Bench | Legal reasoning and analysis tasks | 90.2% | — |
Common questions about Claude 4.6 Opus
What is the context window size for Claude Opus 4.6?
Claude Opus 4.6 has a 1 million token context window, which is currently available in beta. This is the first time the Opus model family has offered a context window of this size.
What is the training data cutoff for Claude Opus 4.6?
Based on the metadata provided, the training date for Claude Opus 4.6 is listed as February 2026. Specific knowledge cutoff details are documented in the model's system card.
What types of tasks is Claude Opus 4.6 best suited for?
Claude Opus 4.6 is designed for demanding, long-horizon tasks including autonomous software development, enterprise workflows, financial analysis, cybersecurity, and complex research. It supports tool use and MCP server integration for agentic pipelines.
Does Claude Opus 4.6 support tool use and external integrations?
Yes. Claude Opus 4.6 accepts tool definitions at inference time and supports MCP (Model Context Protocol) server connections, allowing it to interact with external APIs, data sources, and services.
Where can I access Claude Opus 4.6 via API?
Claude Opus 4.6 is available through Anthropic's API. It is also listed on Azure AI Foundry. The API model reference documentation is available at platform.claude.com.
What people think about Claude 4.6 Opus
Community discussion around Claude Opus 4.6 is generally positive, with the highest-engagement thread focusing on a user-created 3D VoxelBuild benchmark comparing Opus 4.6 to its predecessor, Opus 4.5, and drawing significant interest shortly after the model's release. Users in the r/singularity community appear engaged with benchmark comparisons across frontier models, including Opus 4.6's positioning on coding and reasoning evaluations.
Some threads in the community reference competing models and broader benchmark results, suggesting users are actively tracking how Opus 4.6 performs relative to other releases in the same period. A real-world coding comparison thread on r/LocalLLaMA received lower engagement, indicating that hands-on practical evaluations are discussed but attract a smaller audience than aggregate benchmark discussions.
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Documentation & links
Parameters & options
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. Opus 4.6 uses adaptive thinking mode. The model dynamically decides when and how much to think.
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