Claude Opus 4.6

What is Claude Opus 4.6?

Claude Opus 4.6 is Anthropic’s Opus-class frontier language model, positioned as an upgrade to the company’s previous Opus release. It’s designed to improve performance across agentic coding, computer and tool use, agentic search, and reasoning-intensive work, including finance and other knowledge-work tasks.

The model is meant to handle longer, multi-step tasks more reliably and to operate effectively in larger codebases. Anthropic also notes that Opus 4.6 introduces a 1M token context window (in beta) and adds controls intended to let developers balance intelligence, speed, and cost.

Key Features

• Improved coding performance, including stronger planning and better code review/debugging to catch the model’s own mistakes.
• Longer-horizon “agentic” task execution: Anthropic says the model can sustain agentic tasks for longer sessions.
• More reliable work in larger codebases, with better navigation and change identification for real system tasks.
• 1M token context window in beta for Opus 4.6, enabling larger inputs and longer conversations than prior versions.
• Higher-scoring evaluation results on agentic search and reasoning benchmarks, including Terminal-Bench 2.0 and Humanity’s Last Exam.
• API and product updates for agent workflows, including support for compaction (summarizing its own context), adaptive thinking, and effort controls via the /effort parameter.

How to Use Claude Opus 4.6

• Use Claude Opus 4.6 via claude.ai for interactive work, or access it through the Claude API for developer-driven workflows.
• If you’re using the API, reference the model as claude-opus-4-6.
• For longer-running tasks, Anthropic describes using API compaction to summarize context so the run can continue without immediately hitting limits.
• If the model appears to spend too long on simpler tasks, Anthropic recommends lowering the effort setting from the default high to medium using the /effort parameter.

Use Cases

• Agentic coding with planning and debugging: Use Opus 4.6 to break down complex coding requests into steps and produce code with iterative review and debugging.
• Large-codebase updates: Apply the model to navigate larger repositories and identify the changes needed to address specific requirements.
• Agentic research and information finding: Use Opus 4.6 for multi-step search tasks, particularly when the information is hard to locate and requires deeper reasoning.
• Financial analysis and domain work: Run analysis tasks in finance and other economically valuable knowledge-work settings referenced by Anthropic’s evaluations.
• Document and presentation workflows: Create and edit everyday office deliverables, including documents, spreadsheets, and presentations, with improvements noted for Excel and a PowerPoint research preview.

FAQ

• Is the 1M token context window available for all users? Anthropic specifies it as in beta for Opus 4.6.

• How do I control how much the model thinks? The site describes an /effort parameter; it recommends reducing effort from the default (high) to medium if you find the model overthinking on a task.

• Can Opus 4.6 handle long-running tasks? Anthropic mentions API compaction to summarize its own context and continue longer-running tasks without immediately bumping into limits.

• Where can I access Claude Opus 4.6? It is available on claude.ai, via the API, and on major cloud platforms.

• Is there pricing information on this page? Yes. Pricing is stated as $5 / $25 per million tokens; full details are referenced as being on Anthropic’s pricing page.

Alternatives

• Other frontier or “reasoning” language models: If you’re choosing based on multi-step reasoning and search performance, consider alternative models in the same general class of frontier reasoning systems.
• General-purpose coding/chat models without agentic emphasis: For teams that primarily need shorter coding help rather than long-horizon agentic workflows, a simpler coding-focused model may reduce complexity.
• Specialized tools for search and research workflows: If the main requirement is finding information online, a dedicated retrieval/search workflow (combined with a general model) can be an alternative to relying on a single model for end-to-end agentic search.
• Spreadsheets and document automation solutions: For office productivity tasks, alternatives include spreadsheet/document automation platforms or macros, depending on whether you need natural-language interaction and agentic execution.