Anthropic model
Claude Opus 5.5
Anthropic’s current Opus model for long-running agentic coding and knowledge work, combining a 1M-token context window, 128K output, always-on adaptive thinking, and lower pricing than Claude Opus 5.
- Context window
- 1M
- tokens
- Max output
- 128K
- tokens
- Input
- $4.00
- per 1M tokens
- Cache read
- $0.20
- per 1M tokens
- Output
- $20.00
- per 1M tokens
01 / Overview
What Claude Opus 5.5 Is
Claude Opus 5.5 is Anthropic’s current Opus-tier model for long-running agentic coding and knowledge work, and the provider recommends it as the starting point for most workloads.
The General Frontier Tier Before Fable Escalation
Opus 5.5 occupies a useful middle position in Anthropic’s current lineup. Sonnet 5.5 is cheaper and faster, while Fable 5.1 is more expensive and reserved for demanding reasoning and long-horizon work that still falls short on Opus.
That makes Opus 5.5 the practical frontier baseline: strong enough for difficult coding, code review, research, and knowledge work without immediately paying Fable pricing.
The model provides a 1,000,000-token context window, supports up to 128,000 output tokens, accepts text and images, and uses adaptive thinking on every request. Its default effort is medium, and Anthropic classifies comparative latency as moderate.
Anthropic released Claude Opus 5.5 on September 22, 2026 and lists it as Active (latest), with retirement not sooner than September 22, 2027.
- Current Opus model and recommended starting point for most workloads.
- 1M context window and 128K maximum output.
- Text and image input with text output.
- Adaptive thinking is always on.
- Lower standard token pricing than Claude Opus 5.
- Provider
- Anthropic
- Family
- Claude Opus 5.5
- Model ID
- claude-opus-5-5
- Knowledge cutoff
- Jun 2026
- Input modalities
- Text, Image
- Output modality
- Text
- Default effort
- Medium
02 / Agentic coding
Claude Opus 5.5 for Agentic Coding and Code Review
Anthropic positions Opus 5.5 as especially strong on multistep software-engineering work carried through a real repository until the task is actually complete.
Measure Completed Work, Not One Clever Response
A production coding agent does more than generate a code snippet. It must inspect the repository, understand dependencies, plan changes, edit multiple files, call tools, run tests, investigate failures, and continue until the implementation satisfies the task.
Anthropic reports that Opus 5.5 at its default medium effort can match or beat Opus 5 at high effort on coding evaluations while using fewer steps and fewer tokens. The provider also says output generation is more than 30% faster than Opus 5 and that the model tends to complete the same task with fewer tokens.
Code review is another important use case. Anthropic reports stronger bug detection with fewer false alarms than Opus 5 in early testing. For a review workflow, this should be evaluated on accepted findings: useful bugs found, false positives, severity accuracy, and whether explanations are actionable.
The practical comparison is therefore not simply intelligence per response. Compare end-to-end engineering outcomes: completion rate, number of tool calls, test-pass rate, human interventions, total tokens, and wall-clock time.
- 01
Multi-file implementation
Carry a feature or fix across source files, tests, configuration, and dependencies until validation passes.
- 02
Code review
Find actionable defects while minimizing noisy or low-confidence findings that waste developer time.
- 03
Large migrations
Work through repetitive but stateful changes across a codebase while preserving project-level intent.
- 04
Parallel subagents
Coordinate longer autonomous work where multiple investigation or implementation threads run with limited oversight.
03 / Knowledge work
Knowledge Work With Better Factual Discipline
Opus 5.5 is designed not only for coding but also for knowledge-intensive work where factual precision, source handling, and sustained synthesis matter.
Accuracy Matters More Than Fluent Presentation
Research and professional knowledge work often fail in subtle ways. A model can produce a polished answer while using the wrong number, attributing a claim to the wrong source, or carrying an early assumption through the rest of the analysis.
Anthropic’s prompting guidance says Opus 5.5 is less likely than Opus 5 to state an incorrect figure or cite the wrong source. This makes it a relevant candidate for research synthesis, financial and operational analysis, policy review, document-heavy decision support, and other workflows where factual slips are costly.
The 1M context window allows a large body of source material to remain available during the task, but evaluation should still measure retrieval and attribution quality. A model that can technically receive a million tokens is not automatically guaranteed to use every relevant detail correctly.
For high-value knowledge work, score source fidelity, numerical accuracy, contradiction handling, unsupported claims, and whether the final output makes it easy for a reviewer to verify important conclusions.
- 01
Research synthesis
Combine large bodies of evidence while preserving distinctions between sources and avoiding unsupported conclusions.
- 02
Document analysis
Work across long reports, policies, contracts, technical specifications, and internal reference material.
- 03
Quantitative review
Check figures, assumptions, tables, and claims where small factual errors can invalidate the final recommendation.
- 04
Decision support
Turn complex evidence into a structured recommendation while keeping reasoning traceable to the supplied material.
04 / Pricing
Claude Opus 5.5 Pricing
Claude Opus 5.5 costs $4 per million input tokens and $20 per million output tokens, a 20% reduction from Claude Opus 5’s $5/$25 standard rates.
Frontier Capability With Lower Opus Economics
The base-price reduction matters because difficult agentic tasks often involve many turns rather than one request. A modest difference per million tokens can compound across repeated tool calls, repository context, research material, and long generated outputs.
Prompt caching can lower repeated-context cost further. Anthropic lists 5-minute cache writes at $5 per million tokens, 1-hour cache writes at $8 per million, and cache reads at $0.20 per million.
Batch API input and output receive a 50% discount, making offline evaluation, large-scale analysis, and non-interactive processing materially cheaper than standard synchronous traffic.
For agentic systems, compare cost per completed task. Include uncached input, cache writes, cache reads, output, retries, tool loops, and failed trajectories rather than reducing the comparison to headline token rates.
- Input: $4.00 per 1M tokens.
- Output: $20.00 per 1M tokens.
- 5-minute cache write: $5.00 per 1M tokens.
- 1-hour cache write: $8.00 per 1M tokens.
- Cache read: $0.20 per 1M tokens.
- Batch API: 50% discount on input and output.
1M tokens · USD
- Input
- $4.00
- 5m cache write
- $5.00
- 1h cache write
- $8.00
- Cache read
- $0.20
- Output
- $20.00
Example: 20K input + 4K output
- Input cost
- $0.0800
- Output cost
- $0.0800
- Estimated uncached total
- $0.1600
05 / Context
1M Context and 128K Standard Output
Claude Opus 5.5 has a 1,000,000-token context window and supports up to 128,000 output tokens in standard requests.
Large Enough for Repository, Research, and Agent State
A 1M-token working context can combine source code, long documents, conversation history, tool results, system instructions, images, and intermediate findings without immediately forcing aggressive truncation.
This is especially useful for long-running agents because context can accumulate over many steps. It is also relevant to research and review tasks where the model needs to compare evidence distributed across large source collections.
Anthropic additionally offers a beta path for up to 300,000 output tokens through the Message Batches API using the documented output-300k-2026-03-24 beta header. That capacity is specific to batch processing and should not be confused with the normal 128K maximum output.
Large capacity should still be managed deliberately. Prompt caching, context selection, retrieval quality, and clear separation of instructions from evidence remain important even when the technical ceiling is high.
- Context window: 1,000,000 tokens.
- Standard maximum output: 128,000 tokens.
- Batch API maximum output: up to 300,000 tokens in beta.
- Minimum cacheable prompt length: 512 tokens.
Context window
1,000,000
Standard max output
128,000
The Batch API can support up to 300K output tokens with Anthropic’s documented beta header; standard requests use the 128K output limit.
06 / Thinking & effort
Adaptive Thinking Is Always On
Claude Opus 5.5 always uses adaptive thinking. The main control for balancing intelligence, latency, and cost is the effort level, which defaults to medium.
Medium Is the New Opus Baseline
This default matters when migrating from Claude Opus 5, which defaults to high effort. Carrying the old effort value forward without evaluation can change token consumption and latency in unexpected ways.
Anthropic recommends starting Opus 5.5 at medium and running an effort sweep on real evals rather than assuming that the same label represents the same amount of computation across model generations.
The provider reports that Opus 5.5 at medium can match or exceed Opus 5 at high on coding and knowledge-work evaluations. For some coding evaluations, low comes close at materially lower cost.
Higher effort is still useful for difficult reasoning, but the decision should be driven by marginal outcome quality: does additional effort reduce failures, improve review findings, strengthen research accuracy, or eliminate human intervention enough to justify the extra compute?
Default frontier workload
Start at medium and measure quality, latency, and cost before increasing effort.
Hard reasoning or agent step
Raise effort where the additional thinking measurably improves completion rate, correctness, or review quality.
07 / Opus 5 → 5.5
Migrating From Claude Opus 5 to Opus 5.5
Opus 5.5 lowers pricing and improves performance, but the upgrade is not a pure model-ID swap for applications that depend on thinking configuration, forced tools, computer use, or streamed progress text.
Four Breaking Changes Need Explicit Testing
First, thinking cannot be disabled. Opus 5.5 uses adaptive thinking on every request, so integrations should control depth through effort rather than old thinking modes or token budgets.
Second, forced tool choice is no longer accepted. Applications using tool_choice values that force any tool or a named tool need to move to automatic selection together with strict tool use or structured outputs where appropriate.
Third, thinking blocks are tied to the model and conversation. Routers, fallbacks, or edited histories need to account for thinking-block compatibility when traffic moves between models.
Fourth, on the Claude API and Google Cloud, Opus 5.5 requires the newer computer_toolset_20260801 computer-use interface instead of the earlier computer_20251124 tool.
There is also a response-shape change: text between tool calls may appear in thinking blocks whose text is empty at the default display setting. Applications that previously surfaced that text as progress updates should test streaming behavior explicitly.
- 01
Recalibrate effort
Opus 5.5 defaults to medium rather than high; benchmark several effort levels instead of copying the old setting.
- 02
Remove forced tool choice
Forced any-tool or named-tool modes return errors and require a different orchestration pattern.
- 03
Handle thinking blocks
Thinking is always present and compatibility matters when routing conversations between model families.
- 04
Update computer use and streaming
Use the supported computer toolset on applicable platforms and verify progress text between tool calls.
08 / Capabilities
Claude Opus 5.5 Capabilities
Opus 5.5 combines multimodal input, large context, always-on adaptive reasoning, tool use, prompt caching, batch processing, and very large output capacity for advanced software and knowledge workflows.
A Broad Frontier Integration Surface
Text and image input let the model work across repositories, screenshots, diagrams, document images, tables, and other visual evidence together with written instructions.
Tool use supports agentic workflows, while structured output patterns and strict tool use can provide machine-readable contracts for downstream software. Prompt caching reduces the cost of large repeated prefixes such as repository context, policies, or long system instructions.
The model is available through the Claude API, Amazon Bedrock, Google Cloud, Microsoft Foundry, and Claude Platform on AWS. Anthropic also documents Fast mode as a lower-latency research preview with separate pricing, which should be evaluated separately from standard Opus 5.5 economics.
- Supported
Text
Accept text input and generate text output.
- Supported
Image input
Analyze screenshots, diagrams, document images, and other supported visual material.
- Supported
Adaptive thinking
Thinking is always on and controlled through effort.
- Supported
Tool use
Supports agentic tool workflows, with restrictions on forced tool choice.
- Supported
Prompt caching
Cache reads cost $0.20/MTok, useful for repeated large contexts.
- Supported
Batch API
Batch processing receives a 50% input/output discount and can expose 300K output in beta.
- Supported
Large output
Standard requests support up to 128K output tokens.
09 / Evaluation
Claude Opus 5.5 Strengths and Limitations
Opus 5.5 is Anthropic’s default frontier starting point: substantially cheaper than Fable 5.1 and stronger than the prior Opus generation, but still more expensive and slower than Sonnet 5.5 for workloads that do not need the extra capability.
Strengths
Strong agentic coding baseline
Anthropic positions Opus 5.5 for repository-scale implementation, long-running autonomous work, and stronger code review.
Knowledge-work accuracy
The model is designed to reduce factual and source-attribution errors in difficult professional analysis.
1M context and 128K output
Large working memory and output capacity support complex repositories, research, documents, and agent state.
Improved Opus economics
$4/$20 pricing is lower than Opus 5, with $0.20/MTok cache reads and 50% Batch discounts.
What to consider
More expensive than Sonnet 5.5
Routine workloads may not justify paying twice Sonnet’s standard token price if evaluations show similar accepted-result quality.
Not the maximum capability tier
Anthropic recommends Fable 5.1 when demanding reasoning or long-horizon agentic work still fails on Opus 5.5 at higher effort.
Always-on thinking changes integration behavior
Thinking cannot be disabled, and model-specific thinking blocks require care in routers, fallbacks, and edited conversations.
Migration has breaking API changes
Forced tool selection, computer-use versions, and progress-text handling need explicit testing when upgrading from Opus 5.
Start with the frontier baseline
Evaluate Claude Opus 5.5 on your real workload
Run repository-scale coding tasks, code review, research, document analysis, tool workflows, and long-context prompts, then compare quality, effort, latency, cache usage, and total cost against Sonnet or Fable.
Start FreeAnthropic recommends Opus 5.5 as the starting point for most workloads. Use evals to decide whether Sonnet is sufficient or Fable 5.1 is justified.
Common Questions
What is Claude Opus 5.5?
Claude Opus 5.5 is Anthropic’s current Opus model for long-running agentic coding and knowledge work. Anthropic recommends starting with Opus 5.5 for most workloads before escalating to Fable 5.1.
How much does Claude Opus 5.5 cost?
Claude Opus 5.5 costs $4 per 1M input tokens and $20 per 1M output tokens. Five-minute cache writes cost $5/MTok, one-hour cache writes cost $8/MTok, and cache reads cost $0.20/MTok. Batch input and output receive a 50% discount.
What is the Claude Opus 5.5 context window?
Claude Opus 5.5 has a 1,000,000-token context window and supports up to 128,000 output tokens in standard requests. The Message Batches API can support up to 300,000 output tokens through a beta feature.
What is Claude Opus 5.5’s knowledge cutoff?
Anthropic lists June 2026 as the reliable knowledge cutoff and training-data cutoff for Claude Opus 5.5.
Does Claude Opus 5.5 support images?
Yes. Claude Opus 5.5 accepts text and image input and generates text output.
Does Claude Opus 5.5 use adaptive thinking?
Yes. Adaptive thinking is always on and cannot be disabled. The default effort level is medium, and effort should be calibrated against the workload.
How is Claude Opus 5.5 different from Claude Opus 5?
Opus 5.5 lowers standard pricing from $5/$25 to $4/$20, defaults to medium effort instead of high, uses always-on adaptive thinking, improves long-running coding and knowledge work, and introduces breaking changes around thinking, forced tool use, computer use, and response handling.
Should I choose Claude Opus 5.5 or Claude Fable 5.1?
Anthropic recommends starting with Opus 5.5 for most workloads. Fable 5.1 is the escalation tier for demanding reasoning and long-horizon agentic work when Opus 5.5 at higher effort still fails your evaluations.
Should I choose Claude Opus 5.5 or Claude Sonnet 5.5?
Sonnet 5.5 is faster and costs half as much at $2/$10, while Opus 5.5 is positioned for stronger long-running agentic coding and knowledge work. Run the same evaluation set and compare accepted-result quality, latency, and total cost.
Can Claude Opus 5.5 force a specific tool call?
No. Anthropic’s migration documentation states that forced any-tool and named-tool choices are incompatible with Opus 5.5. Use automatic tool selection with strict tool use or structured output patterns where appropriate.
When was Claude Opus 5.5 released?
Anthropic lists September 22, 2026 as the release date. Retirement is not scheduled sooner than September 22, 2027.
Model information
Last updated
Specifications, pricing, context, thinking behavior, migration changes, and model positioning on this page are based on Anthropic’s official Claude Opus 5.5 overview, prompting guide, migration guide, and current model comparison documentation.