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Claude 3 Opus

Claude 3 Opus

Claude 3 Opus (claude-3-opus-20240229) · Family: Claude
The most capable model of the Claude 3 family (Anthropic, 2024): multimodal (text+image), 200K context, RLHF and Constitutional AI. Now a legacy generation.
⚠ Deprecated⏳ Limited accessLLMMultimodalTool-using model📁 Claude
Context window
200K
tokens
Release date
4 March 2024
Access:APIHostedDeployment:☁ Cloud

Overview

Claude 3 Opus is a large language model from Anthropic, the most capable variant of the Claude 3 family, introduced on 4 March 2024 alongside the Sonnet and Haiku models. It was positioned as Anthropic’s most intelligent model at launch, intended for complex tasks: research, strategy, analysis and automation.

The model is multimodal — it takes text and images (photos, charts, diagrams, documents/PDFs) as input and produces text responses. It supports a 200,000-token context window (with the ability to handle inputs exceeding 1 million tokens for select customers).

Claude 3 Opus was trained using reinforcement learning from human feedback (RLHF) and Anthropic’s Constitutional AI method. The model supports tool use, structured output and multilingual work.

The model was available commercially through the Claude API, the claude.ai platform, and Amazon Bedrock and Google Vertex AI. API pricing was USD 15 per 1M input tokens and USD 75 per 1M output tokens. Claude 3 Opus is now a legacy (deprecated) model, superseded by newer Claude models.

Classification
LLMMultimodalTool-using model
Family: Claude
Access & deployment
APIHosted
Cloud
Weights: Closed
Key parameters
📏 Context: 200K
Tools
📥 Input: text, image, documents

Technical specification

Context window
200K
tokens
License
Proprietary
Features:Tool use
Modalities
⬇ Input
textimagedocuments
⬆ Output
textcodestructured_data

Capabilities and applications

Native model capabilities
Reasoning
The model's ability to reason logically and solve complex problems.
Category: reasoning
Multi-step reasoning
Carrying out multi-step chains of reasoning across long, complex tasks.
Category: reasoning
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
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
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
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

Deployment and security

🔒 Security / Enterprise
✓ Verified enterprise information
Updated: 24 Jul 2026↗ Security documentation