Quick Answer
Claude Opus 5.5 lowers Anthropic’s API pricing while expanding context to 1 million tokens and maximum output to 128,000 tokens. Anthropic says the model costs 40% less to run than Opus 5 and is available through Claude plans and major cloud platforms. Developers should compare workload costs and test outputs before moving production systems carefully.
Key Takeaways
- Claude Opus 5.5 is the first model in Anthropic’s Claude 5.5 family.
- The API costs $4 per million input tokens and $20 per million output tokens.
- Claude Opus 5.5 supports a 1 million-token context window and 128,000-token maximum output.
- Adaptive thinking is always enabled and cannot be disabled for Claude Opus 5.5.
- Anthropic reports more than 30% faster output than Claude Opus 5, while Fast mode can reach up to 2.5 times the speed.
What is Claude Opus 5.5?
Claude Opus 5.5 is Anthropic’s first release in the Claude 5.5 model family, announced on September 22, 2026. Anthropic says the new model reaches Claude Fable 5.1-level performance on most work while costing 40% less to run than Claude Opus 5. Anthropic’s launch announcement describes the release as its new flagship model for complex work.
Claude Opus 5.5 matters primarily for users whose work requires long documents, large codebases, multi-step analysis, or extended agent workflows. A larger context window allows a model to consider more material in one request, which can reduce the need to repeatedly split, summarize, and resend source material. Context capacity alone does not guarantee a correct answer, however, so users still need to review outputs that affect code, legal decisions, financial decisions, or customer-facing material.
Claude Opus 5.5 is available in Claude for Pro, Max, Team, and Enterprise users. Anthropic also makes the model available through the Claude API, Amazon Bedrock, Google Cloud, and Microsoft Foundry. That broad availability gives organizations several deployment options, but access and administrative controls can differ by plan and cloud provider.
How much does Claude Opus 5.5 cost through the API?
Claude Opus 5.5 costs $4 per million input tokens and $20 per million output tokens through Anthropic’s API list pricing. Cache-read tokens cost $0.20 per million tokens, according to the Claude Opus 5.5 model documentation. Input tokens are the material sent to the model, while output tokens are the response the model generates.
Claude Opus 5.5 pricing matters because output-heavy workflows can cost substantially more than requests that mainly process existing text or code. A coding agent that generates large patches, explanations, test files, and revisions can use more output tokens than a short chat request. Teams should measure both sides of usage before estimating monthly spending.
Anthropic also offers an optional Fast mode in Claude Code and the Claude Platform. Fast mode costs $8 per million input tokens and $40 per million output tokens, which is double the standard API list price for both input and output. The higher price can make sense for time-sensitive development workflows, but standard mode remains the more cost-conscious option when response latency is less important.
| Claude Opus 5.5 option | Input price | Output price | Best fit |
|---|---|---|---|
| Standard API mode | $4 per million tokens | $20 per million tokens | General production workloads where cost control matters |
| Fast mode | $8 per million tokens | $40 per million tokens | Time-sensitive Claude Code and Claude Platform tasks |
| Cache reads | $0.20 per million tokens | Not applicable | Repeated use of cached context |
What does the 1 million-token context window change?
Claude Opus 5.5 supports a 1 million-token context window, which is the amount of text, code, and other supported input a request can provide for the model to consider. Anthropic also sets a maximum output of 128,000 tokens. Those limits give developers more room to keep related material in a single workflow rather than dividing it into many smaller requests.
A 1 million-token context window can be useful for large repositories, extensive technical documentation, long policy collections, or large sets of research notes. The practical benefit is continuity: the model can reference more of the supplied material while responding to a task. The practical limit is that a large context does not remove the need to identify the relevant source material or verify the model’s conclusions.
Claude Opus 5.5 may be particularly relevant to teams building agent workflows that must preserve instructions, prior work, and source documents across a long task. Anthropic says an early tester completed a 680,000-line code migration in less than a day, work the company said would otherwise have taken an engineering team weeks. That example is a company-reported early test result, not a guarantee that every migration will produce the same outcome.
Developers considering large-context work should define what success means before expanding usage. A useful evaluation can check whether the model identifies the right files, follows repository rules, preserves tests, and produces reviewable changes. Teams working with parallel coding tasks may also want to evaluate the parallel AI work features in Claude Code alongside the new model’s larger context capacity.
How fast is Claude Opus 5.5 compared with Claude Opus 5?
Claude Opus 5.5 generates output more than 30% faster than Claude Opus 5, according to Anthropic. Claude Opus 5.5 also has an optional Fast mode that Anthropic says can run at up to 2.5 times the speed in Claude Code and the Claude Platform. Faster generation can reduce waiting time in iterative coding and analysis work, especially when users need several revisions.
Claude Opus 5.5 speed figures should be treated as vendor-reported performance claims rather than universal results. Actual response times can vary with prompt size, output length, tool calls, platform configuration, and demand on the service. A shorter response time also does not establish that an answer is more accurate or that generated code is safe to deploy.
The most sensible approach is to test a representative workload in both standard mode and Fast mode. Measure the full task time, not only the first response, because a slower initial answer can still be more efficient if it requires fewer corrections. Organizations should also compare the higher Fast mode token rates against the time savings their teams actually receive.
What benchmark results did Anthropic report for Claude Opus 5.5?
Claude Opus 5.5 scored 66.4% on Anthropic’s reported Terminal-Bench 4.0 evaluation, compared with 52.3% for Claude Opus 5 and 57.9% for OpenAI’s GPT-6 Astra. Anthropic reports those figures as benchmark results, and the company cautions that benchmark margins are becoming less reliable as a guide to real-world differences. The figures are therefore self-reported and should not be treated as a complete comparison of model quality.
Terminal-Bench is relevant because it assesses agent-style computer tasks rather than only short-answer knowledge questions. A higher reported score can indicate better performance on the specific tasks included in that evaluation. The limitation is that benchmarks test defined conditions, while real deployments involve different tools, instructions, access permissions, and failure consequences.
Claude Opus 5.5 should be evaluated against the work a team actually performs. Software teams can test issue triage, code changes, test generation, and documentation updates. Business users can test research synthesis, structured drafting, and document review, while keeping sensitive data out of prompts unless their organization has approved the relevant data handling and access controls.
Model comparisons also change quickly as providers update products and add new capabilities. Readers comparing competing systems can consider how Grok’s reasoning controls and context tools address different workflow needs, but direct comparisons need equivalent prompts, consistent evaluation criteria, and careful human review.
How does adaptive thinking work in Claude Opus 5.5?
Claude Opus 5.5 uses adaptive thinking that is always on and cannot be disabled. Anthropic describes adaptive thinking as part of the model’s operation, meaning users do not need to manually select a separate thinking setting before making a request. The design can simplify access to reasoning behavior, but it also gives users less direct control over that specific model setting.
Adaptive thinking matters because complex prompts often need more than a direct retrieval or short completion. A model may need to interpret constraints, compare alternatives, plan steps, or reconcile information within the supplied context. The feature does not change the need for a clear prompt, accurate source material, and human review of any output that creates operational, legal, medical, or security consequences.
Claude Opus 5.5 also includes preserved-thinking anti-distillation safeguards for eligible newer API accounts, according to Anthropic. The company says external evaluators Frontier Design and METR tested the model before release. Those measures provide information about Anthropic’s release process, but organizations remain responsible for setting their own approval process, access limits, and review requirements.
Who should use Claude Opus 5.5?
Claude Opus 5.5 is most relevant to developers, organizations, and advanced Claude users who need large-context analysis, substantial code generation, or repeated multi-step work. The combination of a 1 million-token context window, 128,000-token maximum output, and lower API list pricing gives the model a clearer case for workloads that would otherwise require many fragmented requests.
Claude Pro, Max, Team, and Enterprise users can access Claude Opus 5.5 in Claude, while API customers can use it directly or through supported cloud services. Reuters also reported the September 22 launch and Anthropic’s effort to pair stronger performance with lower operating costs. Reuters’ launch report provides additional context on the release.
Claude Opus 5.5 is not automatically the best choice for every request. Short, simple tasks may not need a flagship model’s context capacity or output limit. The practical response is to assign Claude Opus 5.5 to tasks where broader context, more substantial output, or faster iterative work produces a measurable benefit, then use smaller or lower-cost options where those capabilities are unnecessary.
Security-sensitive teams should also treat AI model access as part of their broader security program. Account permissions, connected tools, and uploaded material can create risks beyond the model itself, as shown by research involving AI-assisted account breaches. Stop and involve an organization’s security or compliance team before connecting a model to production systems, privileged accounts, or confidential data.
FAQ
Is Claude Opus 5.5 available now?
Claude Opus 5.5 is available as of its September 22, 2026 launch for Claude Pro, Max, Team, and Enterprise users, plus API customers and supported cloud platforms. Availability can still depend on the specific account, provider, and administrative configuration.
How much does Claude Opus 5.5 cost?
Claude Opus 5.5 costs $4 per million input tokens and $20 per million output tokens through the standard API. Anthropic lists cache-read tokens at $0.20 per million tokens and Fast mode at $8 input and $40 output per million tokens.
Does Claude Opus 5.5 have a 1 million-token context window?
Claude Opus 5.5 has a 1 million-token context window and a 128,000-token maximum output. The larger context can help with large repositories and long documents, but users still need to verify important outputs.
Can adaptive thinking be turned off in Claude Opus 5.5?
Claude Opus 5.5 adaptive thinking cannot be turned off. Anthropic says the feature is always enabled, so users should evaluate the model’s behavior using their own representative prompts and workflows.
Is Claude Opus 5.5 faster than Claude Opus 5?
Claude Opus 5.5 generates output more than 30% faster than Claude Opus 5, according to Anthropic. Fast mode can reach up to 2.5 times the speed, but it costs more and real performance depends on the workload.