Complete Claude Opus 5.5 Guide

Claude Opus 5.5 is Anthropic’s latest Opus model, released on September 22, 2026.

It is designed for demanding coding, AI agents, computer use, professional knowledge work, financial analysis, research, and complex multi-step tasks.

Anthropic positions it as its strongest Opus model yet.

• Agentic coding
• Complex reasoning
• Long-running tasks
• Large codebase work
• AI agents
• Multi-tool workflows
• Computer use
• Professional knowledge work
• Financial analysis
• Document analysis
• Research and synthesis
• Visual understanding
• Spreadsheet, presentation, and document workflows
• Following detailed instructions
• Clear professional writing

• 20% lower input token price
• 20% lower output token price
• 60% cheaper cache reads
• About 40% lower cost on typical workloads at default settings
• More than 30% faster output generation
• Better agentic coding performance
• Better computer-use capabilities
• Better knowledge-work performance
• Greater token efficiency
• Fewer steps for many agentic tasks
• Clearer and more natural communication
• Better performance on long-running projects

Claude Opus 5.5 uses adaptive thinking.

The model dynamically determines how much reasoning a task requires instead of treating every request equally.

Medium is the default effort level.

Higher effort can improve performance on difficult tasks but generally increases latency and token consumption.

Low

Use for simpler tasks.

Medium

Use for most everyday professional work.

High or XHigh

Use for difficult coding, analysis, and agentic workflows.

Max

Reserve for exceptionally difficult tasks where quality matters more than cost or speed.

Opus 5.5 is particularly strong at agentic software engineering.

• Build features
• Debug complex issues
• Refactor code
• Review pull requests
• Navigate large repositories
• Run terminal workflows
• Investigate root causes
• Write tests
• Fix failing tests
• Perform codebase-wide migrations
• Work across multiple files
• Explain its modifications
• Execute long-running engineering tasks

Opus 5.5 is built for workflows where Claude needs to do more than simply answer a prompt.

• Plan multi-step tasks
• Use tools
• Coordinate subagents
• Navigate applications
• Gather information
• Analyze results
• Take sequential actions
• Check its own work
• Maintain progress across long tasks
• Report what it completed
• Identify what it needs next

This makes it particularly useful for autonomous and semi-autonomous AI agents.

Opus 5.5 combines visual understanding with reasoning for computer-based workflows.

• Websites
• Software interfaces
• Screenshots
• Documents
• Charts
• Dashboards
• Diagrams
• Multiple applications

This allows agents built around the model to perform multi-step digital workflows that require both perception and judgment.

Opus 5.5 is designed for serious professional work such as:

• Market research
• Competitive analysis
• Strategy
• Financial research
• Data interpretation
• Document synthesis
• Business analysis
• Report generation
• Planning
• Decision support
• Due diligence
• Complex research

Anthropic reports an Elo score of 1,846 on GDPval-AA v2.1, which evaluates real-world professional work across dozens of occupations.

• Reading financial filings
• Analyzing financial models
• Reviewing charts
• Comparing companies
• Extracting financial information
• Research synthesis
• Scenario analysis
• Creating financial summaries
• Supporting reporting workflows

Human verification remains important for financial decisions and compliance-sensitive outputs.

Opus 5.5 can reason across visual information such as:

• Screenshots
• Charts
• Graphs
• Diagrams
• Documents
• Tables
• Interface layouts
• Complex imagery

This makes it useful when text and visual information need to be understood together.

Opus 5.5 is designed to communicate more naturally than earlier Opus models.

• Put important information first
• Follow writing constraints
• Produce clearer explanations
• Reduce unnecessary jargon
• Maintain instructions across longer sessions
• Produce professional business writing

It can be used for reports, documentation, research summaries, marketing material, proposals, strategy documents, and other professional writing.

One of its major strengths is handling large, sprawling projects.

• Repository-wide code migrations
• Large code audits
• Multi-stage research
• Complex business analysis
• Agent workflows involving many tools
• Large document collections
• End-to-end software projects

The advantage is not simply answering difficult questions. It is maintaining useful performance across many interconnected steps.

Opus 5.5 is particularly suited to Claude Code.

• Building applications
• Exploring unfamiliar repositories
• Debugging
• Refactoring
• Testing
• Code review
• Architecture analysis
• Large migrations
• Terminal automation
• Complex multi-file implementation

For difficult engineering projects, give Claude a clear objective, constraints, testing requirements, and definition of completion.

API model ID:

claude-opus-5-5

Input

$4 per 1 million tokens

Output

$20 per 1 million tokens

Cache reads

$0.20 per 1 million tokens

5-minute cache writes

$5 per 1 million tokens

1-hour cache writes

$8 per 1 million tokens

Prompt caching can significantly reduce the cost of workloads repeatedly using the same large context.

Opus 5.5 also offers Fast Mode for supported Claude Code and Claude Platform usage. It can provide up to approximately 2.5x faster generation.

Input

$8 per 1 million tokens

Output

$40 per 1 million tokens

Use Fast Mode when latency matters more than minimizing token costs.

• Claude
• Claude Code
• Claude Platform
• Claude API
• Amazon Web Services
• Google Cloud
• Microsoft Foundry

In Claude, Opus 5.5 is available to eligible Pro, Max, Team, and Enterprise users.

1. Role

Tell Claude what expertise or perspective the task requires.

2. Objective

Clearly describe the final result you need.

3. Context

Provide the information Claude needs to understand the situation.

4. Input

Give Claude the documents, data, code, requirements, or other source material.

5. Constraints

Specify what Claude must and must not do.

6. Process

For complex workflows, describe important stages or requirements.

7. Output

Define exactly what the finished answer should contain.

8. Quality bar

Explain what a successful result looks like.

Role: Act as [role/expertise]. Objective: Complete [specific objective]. Context: Here is the relevant background: [context]. Input: Use the following information: [input]. Requirements: Follow these requirements: [requirements]. Constraints: Do not [constraints]. Process: Analyze the task carefully, use available tools where appropriate, verify important assumptions, and check your work before completing the task. Output: Return the result as [desired format]. Success criteria: The result should be [accuracy, completeness, tone, depth, or other quality requirements].

• Give Claude a specific goal
• Provide relevant context
• Define success clearly
• Separate instructions from source material
• Specify your desired output structure
• Give examples when formatting matters
• Use structured sections for complex prompts
• Provide tools when external actions are required
• Tell Claude what it is allowed to change
• Define boundaries for autonomous tasks
• Ask it to verify completed work
• Use prompt caching for repeated large contexts
• Match reasoning effort to task difficulty
• Avoid Max effort when simpler settings already solve the task

• Writing
• Summarization
• Research synthesis
• Everyday coding
• Document analysis
• Business analysis
• General professional work

• Complex debugging
• Difficult coding
• Architecture decisions
• Large codebase changes
• Deep research
• Complex financial analysis
• Multi-step agents
• Difficult reasoning
• Computer-use agents

• Extremely difficult reasoning
• Hard engineering problems
• High-complexity agentic tasks
• Problems where additional reasoning is worth the extra cost and latency

Developers

Coding, debugging, refactoring, migrations, code review, architecture, and autonomous engineering.

Businesses

Research, analysis, reports, documents, spreadsheets, presentations, workflows, and agents.

Researchers

Literature analysis, synthesis, data interpretation, research planning, and complex reasoning.

Analysts

Financial analysis, market research, competitive intelligence, document analysis, and reporting.

Creators

Research, ideation, scripting, editing, content repurposing, and structured knowledge extraction.

AI Builders

Tool-using agents, coding agents, browser agents, enterprise workflows, computer-use systems, and multi-agent systems.

Opus 5.5 can be unnecessary for simple high-volume tasks.

For tasks such as basic classification, short extraction, simple rewriting, straightforward summarization, or massive repetitive workloads, a smaller and cheaper model may provide better economics.

Use Opus 5.5 when the additional intelligence, reasoning, reliability, coding capability, or agentic performance provides meaningful value.

• It can still make factual mistakes
• Generated code still requires testing
• Research claims should still be verified
• Tool-using agents can take incorrect actions
• More reasoning does not guarantee correctness
• Higher effort increases computational cost
• Benchmark leadership does not guarantee superiority on every real-world task
• Sensitive financial, legal, medical, security, and other high-stakes work still requires appropriate human review