Claude Opus 5.5 API

anthropic/claude-opus-5.5
1M tokens · 640 input / 3200 output credits / 1M tokens

Claude Opus 5.5 turns text and images into code and analysis, combining a million-token context with adaptive reasoning for multi-step work. Provide source files, charts, and acceptance criteria to keep its responses focused on your objective and key constraints.

Claude Opus 5.5

Anthropic · chat-completions

Chat with Claude Opus 5.5

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Claude Opus 5.5

Claude Opus 5.5 is an Anthropic model for long-running coding and knowledge work, using adaptive reasoning to process code, documents, and visual evidence. Its million-token context holds connected source files, reference material, and conversation history for tracing dependencies, comparing findings, and drafting reviewable code and analysis. Use Claude Messages or Chat Completions to add evidence and review results across successive turns.

Why Choose Claude Opus 5.5?

  • Long-running coding tasksCombine connected files, architecture rules, and test results to trace dependencies, plan migrations, diagnose issues, and review multi-step changes.

  • Million-token contextKeep source files, reference documents, and conversation history together so analysis can consider constraints and evidence spread across multiple materials.

  • Chart and screenshot understandingSubmit text and image blocks through Claude Messages to analyze chart data and interface states alongside your question.

  • Adaptive reasoningThe model allocates thinking depth to the task. Adjust output_config.effort through Claude Messages to choose a level for routine analysis or complex engineering work.

Parameters

ParameterRequirementDescription
messagesRequired

A non-empty ordered conversation array. Claude Messages content accepts strings or text and image blocks.

max_tokensRequired for Claude Messages

A positive integer budgeting the response, including thinking tokens. Model maximum: 128,000 tokens; playground: 1–65,536, default 4,096.

systemOptional

Top-level system instructions as a string or text blocks for Claude Messages; Chat Completions uses a system-role message.

temperatureOptional

The playground offers 0–2 and defaults to 1.

top_pOptional

The playground offers 0–1 and defaults to 1.

output_config.effortOptional

Reasoning effort for Claude Messages: low, medium, high, xhigh, or max; defaults to medium.

cache_controlOptional

Prompt caching for Claude Messages: use type: ephemeral with ttl: 5m or 1h.

toolsOptional

Tool definitions for Claude Messages with name, description, and input_schema. Your application executes tools and returns results in subsequent messages.

streamOptional

Use false for complete JSON or true for an SSE event stream.

Defaultfalsetrue

How to Use

  1. Define the deliverable and review criteriaDescribe the requested code, analysis, or document with the architecture, format, and review requirements it must follow.

  2. Provide relevant evidenceEnter text context in the playground. For image analysis, send text and image blocks in a Claude Messages request.

  3. Choose a protocol and response budgetSelect Chat Completions or Claude Messages, then set System Prompt, Temperature, Max Tokens, and Top P.

  4. Send and review the resultInspect the answer and token usage against your acceptance criteria, then add evidence or ask a follow-up question.

Pricing

Input, output, cache reads, and the two cache-write tiers are metered separately. Every rate below is per 1M tokens.

UsageRateDetails
Input$3.20 · 640 credits / 1M tokensRegular input tokens in the request.
Output$16.00 · 3200 credits / 1M tokensOutput tokens in the response, including thinking tokens.
Cache Read$0.160 · 32 credits / 1M tokensInput tokens read from the prompt cache.
Cache Write (5m)$4.00 · 800 credits / 1M tokensTokens written to a five-minute prompt cache.
Cache Write (1h)$6.40 · 1280 credits / 1M tokensTokens written to a one-hour prompt cache.

Best Use Cases

  • Code migration and refactoringSupply existing implementations, target architecture, and test evidence to trace dependencies and plan migration and verification steps.

  • Long-document synthesisCompare reports, requirements, and technical documents to reconcile findings, identify conflicts, and produce traceable analysis.

  • Chart and interface interpretationSend charts or screenshots through Claude Messages and ask for an explanation of data relationships, interface states, or workflow steps.

Pro Tips

  • Provide the objective, constraints, evidence, and acceptance criteria together, and ask for supporting evidence and verification steps.
  • Keep repeated system instructions and reference material as a stable prefix, append new messages, and set the cache lifetime with cache_control.
  • In Claude Messages tool loops, read response blocks by type, preserve thinking blocks intact, and append tool results to the conversation.

Specifications and Usage

  • The model context window is 1,000,000 tokens, with a maximum output of 128,000 tokens.
  • Playground Max Tokens ranges from 1 to 65,536 and defaults to 4,096; the response budget includes thinking tokens.
  • Adaptive thinking is always active. Claude Messages output_config.effort defaults to medium.
  • The minimum cacheable prompt length is 512 tokens. Inspect response usage for input, output, and cache token counts.

Related Models

Claude Opus 5.5 API Frequently Asked Questions

What is the Claude Opus 5.5 API?

Claude Opus 5.5 is an Anthropic model that turns text and images into code and analysis for long-running coding and knowledge work. It combines a million-token context, adaptive reasoning, and visual understanding for cross-file changes, long documents, and charts. Supply task constraints and adjust reasoning depth with output_config.effort in Claude Messages. You can call it programmatically or try text conversations in the playground above.

How does Claude Opus 5.5 help with code migration?

Give Claude Opus 5.5 the relevant source files, target architecture, compatibility requirements, and test results. Ask it to trace dependencies and outline migration steps before proposing changes and verification. Its long context holds connected task evidence for reviewing multi-file changes across subsequent turns.

How large is the Claude Opus 5.5 context window?

Claude Opus 5.5 has a 1,000,000-token context window for source files, documents, and conversation history. Keep file names, section names, and citation locations in your material so its analysis can refer back to the evidence from different sources.

How does Claude Opus 5.5 analyze charts and screenshots?

Combine text and image blocks in the content of a Claude Messages request. Specify the values to read, regions to compare, or interface state to explain. Claude Opus 5.5 uses the visual content and your question to produce text analysis; see the API view for the request format.

How do I adjust Claude Opus 5.5 reasoning effort?

Set output_config.effort in a Claude Messages request to low, medium, high, xhigh, or max; medium is the default. Adaptive thinking is always active in Claude Opus 5.5. Choose effort for the complexity of your task and leave room in max_tokens for both thinking and the answer.

How do I set the Claude Opus 5.5 output budget?

The Claude Opus 5.5 model maximum is 128,000 output tokens. This playground offers Max Tokens from 1 to 65,536, with a default of 4,096. The budget includes thinking tokens, so choose a value for the task complexity and expected answer length, then inspect usage for actual consumption.

How does Claude Opus 5.5 reuse prompt caching?

Set cache_control on cacheable content in a Claude Messages request with type: ephemeral and ttl: 5m or 1h, and keep the repeated content prefix stable. Claude Opus 5.5 has a minimum cacheable prompt length of 512 tokens. Cache reads and the two cache-write tiers are metered separately at the rates in this page’s pricing table.