Anthropic's most capable model. Industry-leading in agentic coding, research, finance, and tool use — with a 1M token context window and adaptive thinking.
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Upgraded coding skills, deeper reasoning, and longer sustained agentic tasks — all in one model.
Plans more carefully, sustains tasks for longer, operates reliably in larger codebases, and catches its own mistakes with superior debugging skills.
Outperforms all frontier models on BrowseComp for locating hard-to-find information. Leads on Humanity's Last Exam for complex multidisciplinary reasoning.
Outperforms GPT-5.2 by ~144 Elo points on GDPval-AA — an evaluation of economically valuable knowledge work in finance, legal, and other domains.
State-of-the-art results across agentic coding, reasoning, search, and finance evaluations.
Highest score on the agentic coding evaluation
Leads all frontier models on complex multidisciplinary reasoning
Best at locating hard-to-find information online
Outperforms GPT-5.2 by ~144 Elo points on knowledge work
8-needle 1M variant — vs Sonnet 4.5's 18.5%
Averaged over 25 trials on software engineering tasks
A comprehensive set of capabilities designed for developers, researchers, and knowledge workers.
Claude decides when deeper reasoning is helpful. Adjust effort levels (low, medium, high, max) to optimize for intelligence, speed, or cost.
First Opus-class model with 1M token context. Holds and tracks information over hundreds of thousands of tokens with less drift.
Automatically summarizes and replaces older context when conversations approach the threshold, letting Claude perform longer tasks.
Supports outputs of up to 128K tokens, enabling Claude to complete larger-output tasks without breaking them into multiple requests.
Most comprehensive safety evaluations ever run. Low misaligned behavior rates and lowest over-refusal rate of any recent Claude model.
Spin up multiple agents that work in parallel and coordinate autonomously — best for independent, read-heavy work like codebase reviews.
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