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Claude Opus 4.6

With support for massive context windows and scalable agent-based workflows, Claude 4.6 Opus handles tasks beyond standard language models.
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Claude Opus 4.6

Claude 4.6 Opus is Anthropic’s most advanced AI model, built for deep reasoning, long-context analysis, and complex professional workflows.

Claude Opus 4.6 API Overview

Claude Opus 4.6 delivers a step‑change in reliability and intelligent autonomy, combining a million‑token context window (beta), adaptive thinking, and powerful agentic capabilities in one premium model.

What Is Claude 4.6 Opus?

Claude 4.6 Opus is the flagship model in the Claude 4 generation, engineered to handle demanding cognitive workloads that exceed the capabilities of standard large language models. It is optimized for scenarios where precision, consistency, and extended reasoning matter more than speed alone.

Unlike lighter models focused on conversational tasks, Claude 4.6 Opus excels at end-to-end execution: understanding complex inputs, maintaining context over long sessions, and producing structured, high-quality outputs suitable for real-world deployment.

API Pricing

Input

  • ≤ 200K tokens: $6.50
  • > 200K tokens: $13.00

Output

  • ≤ 200K tokens: $32.50
  • > 200K tokens: $48.75

Performance Benchmarks

  • Strong long-context reasoning performance across benchmarks that evaluate sustained attention, multi-step logic, and information retrieval over very large inputs.
  • High accuracy in complex coding benchmarks, including code generation, refactoring, and debugging tasks involving multi-file and multi-module projects.
  • Improved analytical benchmark results in research, legal, and financial scenarios that require structured thinking, consistency, and precise interpretation of data.
  • Stable and coherent output quality in extended evaluations, where maintaining context and reasoning quality over long sessions is critical.
Benchmark table comparing Opus 4.6 to other models

Core Capabilities

Deep Reasoning and Planning

Opus 4.6 is tuned to read the full picture before acting, mapping file structures, dependencies, and patterns so it can plan multi‑step solutions instead of producing shallow, one‑shot answers. It stays with hard problems longer, explores alternatives independently, and commits to a direction once it has enough context, making it suitable for nuanced product, technical, and organizational decisions.

Advanced Coding and Software Engineering

Opus 4.6 delivers production‑ready code with stronger code review, debugging, and large‑codebase navigation than earlier Claude models. It scored at the top of coding evaluations like Terminal‑Bench 2.0 and is designed to autonomously close issues, manage repositories, and coordinate multi‑repo tasks with minimal human hand‑holding.

Bar charts comparing Opus 4.6 to other models on Terminal-Bench 2

Agentic Workflows and Tool Use

The model excels at agentic terminal coding, computer use, and sophisticated tool calling, enabling workflows where it operates software, searches, and internal tools on your behalf. Features like agent teams let multiple Claude Code sessions collaborate on complex tasks, while adaptive thinking decides when to invest more reasoning effort versus returning faster answers.

Professional Creativity and Document Automation

Claude Opus 4.6 can draft, refine, and orchestrate complex documents such as financial analyses, research syntheses, polished decks, and interactive product specs. With tight integrations for Excel and a research preview for PowerPoint, it can pull data from connected tools, chase leads across sources, and assemble presentations or models that reflect the actual underlying information.

Use Cases

Software Development and Engineering

  • Multi‑step coding workflows across large codebases.​
  • Automated code review and self‑debugging, catching and fixing its own mistakes.
  • Agentic terminal coding and IDE integration for tasks like refactors, migrations, and tests.

AI Agents and Operations Automation

  • Long‑horizon agents that manage tasks across tools, repositories, and teams.​
  • Agent teams where multiple Claude instances collaborate on large projects.​​
  • Operational decision support, such as autonomously closing issues and escalating only when needed.

Prompting Best Practices

Anthropic recommends giving Opus 4.6 rich initial context, goals, constraints, examples, and definitions, so it can build an accurate mental model before acting. For complex workflows, you get better results by asking it to outline a plan, validate assumptions, and then execute the plan step by step with checkpoints.

Claude Opus 4.6 API Overview

Claude Opus 4.6 delivers a step‑change in reliability and intelligent autonomy, combining a million‑token context window (beta), adaptive thinking, and powerful agentic capabilities in one premium model.

What Is Claude 4.6 Opus?

Claude 4.6 Opus is the flagship model in the Claude 4 generation, engineered to handle demanding cognitive workloads that exceed the capabilities of standard large language models. It is optimized for scenarios where precision, consistency, and extended reasoning matter more than speed alone.

Unlike lighter models focused on conversational tasks, Claude 4.6 Opus excels at end-to-end execution: understanding complex inputs, maintaining context over long sessions, and producing structured, high-quality outputs suitable for real-world deployment.

API Pricing

Input

  • ≤ 200K tokens: $6.50
  • > 200K tokens: $13.00

Output

  • ≤ 200K tokens: $32.50
  • > 200K tokens: $48.75

Performance Benchmarks

  • Strong long-context reasoning performance across benchmarks that evaluate sustained attention, multi-step logic, and information retrieval over very large inputs.
  • High accuracy in complex coding benchmarks, including code generation, refactoring, and debugging tasks involving multi-file and multi-module projects.
  • Improved analytical benchmark results in research, legal, and financial scenarios that require structured thinking, consistency, and precise interpretation of data.
  • Stable and coherent output quality in extended evaluations, where maintaining context and reasoning quality over long sessions is critical.
Benchmark table comparing Opus 4.6 to other models

Core Capabilities

Deep Reasoning and Planning

Opus 4.6 is tuned to read the full picture before acting, mapping file structures, dependencies, and patterns so it can plan multi‑step solutions instead of producing shallow, one‑shot answers. It stays with hard problems longer, explores alternatives independently, and commits to a direction once it has enough context, making it suitable for nuanced product, technical, and organizational decisions.

Advanced Coding and Software Engineering

Opus 4.6 delivers production‑ready code with stronger code review, debugging, and large‑codebase navigation than earlier Claude models. It scored at the top of coding evaluations like Terminal‑Bench 2.0 and is designed to autonomously close issues, manage repositories, and coordinate multi‑repo tasks with minimal human hand‑holding.

Bar charts comparing Opus 4.6 to other models on Terminal-Bench 2

Agentic Workflows and Tool Use

The model excels at agentic terminal coding, computer use, and sophisticated tool calling, enabling workflows where it operates software, searches, and internal tools on your behalf. Features like agent teams let multiple Claude Code sessions collaborate on complex tasks, while adaptive thinking decides when to invest more reasoning effort versus returning faster answers.

Professional Creativity and Document Automation

Claude Opus 4.6 can draft, refine, and orchestrate complex documents such as financial analyses, research syntheses, polished decks, and interactive product specs. With tight integrations for Excel and a research preview for PowerPoint, it can pull data from connected tools, chase leads across sources, and assemble presentations or models that reflect the actual underlying information.

Use Cases

Software Development and Engineering

  • Multi‑step coding workflows across large codebases.​
  • Automated code review and self‑debugging, catching and fixing its own mistakes.
  • Agentic terminal coding and IDE integration for tasks like refactors, migrations, and tests.

AI Agents and Operations Automation

  • Long‑horizon agents that manage tasks across tools, repositories, and teams.​
  • Agent teams where multiple Claude instances collaborate on large projects.​​
  • Operational decision support, such as autonomously closing issues and escalating only when needed.

Prompting Best Practices

Anthropic recommends giving Opus 4.6 rich initial context, goals, constraints, examples, and definitions, so it can build an accurate mental model before acting. For complex workflows, you get better results by asking it to outline a plan, validate assumptions, and then execute the plan step by step with checkpoints.

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