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Claude Opus 5

Claude Opus 5

Claude Opus 5 (claude-opus-5) · Family: Claude
Anthropic’s flagship model (24 Jul 2026): “thoughtful and proactive”, strong at agentic coding, computer use and research; API $5/$25 per M tokens, Fast mode.
✓ Active✓ Public accessFeaturedLLMMultimodalReasoning modelTool-using model📁 Claude
Release date
24 July 2026
Access:APIHostedDeployment:☁ Cloud

Overview

Claude Opus 5 is Anthropic’s flagship AI model, released on 24 July 2026 as the next generation of the Claude family. Anthropic describes it as a “thoughtful and proactive” model that excels at coding, knowledge work, scientific research and computer-use tasks.

A hallmark of Opus 5 is strong agentic behavior — the model carefully verifies its own work and iterates on a solution, which translates into high quality on complex, multi-step tasks. It accepts text and image input and produces, among other things, visual outputs.

The model is available from launch across all Anthropic platforms: via the Claude API, in the Claude.ai app, and in Claude Code, Claude Cowork and on the Claude Platform. API pricing is $5 per million input tokens and $25 per million output tokens (the same as Opus 4.8); a Fast mode is also available, running about 2.5× faster at twice the base price.

Anthropic presents Opus 5’s results across a range of benchmarks (including Frontier-Bench, CursorBench, ARC-AGI, Zapier AutomationBench, OSWorld and GDPval), positioning it as a frontier-class model for agentic coding, work automation and advanced reasoning.

Classification
LLMMultimodalReasoning modelTool-using model
Family: Claude
Access & deployment
APIHosted
Cloud
Weights: Closed
Key parameters
Tools
📥 Input: text, image, documents

Technical specification

License
Proprietary
Hardware requirements
A proprietary, hosted (cloud) model — delivered as a service via the Claude API, Claude.ai, Claude Code, Claude Cowork and Claude Platform. No local deployment (closed weights).
Features:Tool use
Modalities
⬇ Input
textimagedocuments
⬆ Output
textcodeimage

Capabilities and applications

Native model capabilities
Reasoning
The model's ability to reason logically and solve complex problems.
Category: reasoning
Advanced reasoning
The ability to perform multi-step, structured reasoning: analysing problems, planning steps, and drawing conclusions from hypotheses. Reasoning-first models (e.g. GPT-5.1 Thinking) dedicate a portion of inference to chains of thought before responding.
Category: reasoning
Multi-step reasoning
Carrying out multi-step chains of reasoning across long, complex tasks.
Category: reasoning
Extended thinking mode
A reasoning-model variant with a larger inference budget: more thinking cycles, higher answer precision at the cost of response time. Choice between 'standard' and 'extended' thinking is left to the user (e.g. the selector in GPT-5.2 Pro).
Category: reasoning
Coding
Generating, analysing and modifying code in many programming languages. Covers writing functions, debugging, refactoring, code review, and creating tests. Measured by benchmarks such as HumanEval and SWE-bench.
Category: coding
Agentic coding
Multi-hour, multi-step programming tasks performed autonomously by the model: cloning a repository, running tests, iterating on fixes, integrating with CLI tools. Characteristic of Codex variants (GPT-5.1-Codex-Mini, Codex-Max).
Category: coding
Agentic capability
The model's ability to autonomously plan and execute multi-step tasks by sequentially using tools, maintaining context, and adapting to intermediate results.
Category: planning
Tool use
The model's ability to call external functions, APIs and tools during a conversation: calculator, search engine, code editor, database. The model decides when and how to use a tool and interprets its result.
Category: planning
Computer use
The model's ability to operate a computer interface by interpreting screenshots and generating actions such as clicks, typing, and navigating applications.
Category: planning
Long context
Support for large context windows — tens to hundreds of thousands (or millions) of input tokens. Enables analysis of entire codebases, long documents, and many parallel conversations without losing earlier information. GPT-5.1 supports 400,000 tokens.
Category: language
Structured output
Producing data in structured formats such as JSON.
Category: structured_generation
Image understanding
Analysing and interpreting the content of images.
Category: vision
Chart understanding
Reading and interpreting charts, tables and diagrams.
Category: vision
OCR
Recognising text within images and documents.
Category: vision
Multilingual
Competence in many natural languages (from a few to over a hundred): understanding, generation, translation, and code-switching within a single conversation. Frontier models support a wide range of languages with comparable quality.
Category: language

Pricing

Technical architecture

Core Architecture