Claude Opus 4.5
Version: 20251101
Models from Partners and Community
These models constitute the vast majority of the Azure AI Foundry Models and are provided by trusted third-party organizations, partners, research labs, and community contributors. These models offer specialized and diverse AI capabilities, covering a wide array of scenarios, industries, and innovations. An example of models from Partners and community are the family of large language models developed by Anthropic. Anthropic includes Claude family of state-of-the-art large language models that support text and image input, text output, multilingual capabilities, and vision. See Anthropic's privacy policy to know more about privacy. Learn how to deploy Anthropic models . Characteristics of Models from Partners and Community:- Developed and supported by external partners and community contributors.
- Diverse range of specialized models catering to niche or broad use cases.
- Typically validated by providers themselves, with integration guidelines provided by Azure.
- Community-driven innovation and rapid availability of cutting-edge models.
- Standard Azure AI integration, with support and maintenance managed by the respective providers.
Key capabilities
About this model
Claude Opus 4.5 is Anthropic’s most intelligent model, and an industry leader across coding, agents, computer use, and enterprise workflows.Key model capabilities
- Extended thinking: Extended thinking gives Claude enhanced reasoning capabilities for complex tasks.
- Image & text input: With strong vision capabilities, Claude Opus 4.5 can process images and return text outputs to analyze and understand charts, graphs, technical diagrams, reports, and other visual assets.
- Computer use: Claude Opus 4.5 is Anthropic’s most accurate model for computer use, enabling developers to direct Claude to use computers the way people do.
- Advanced tool use: Build agents that can take action with three new capabilities–the tool search tool, programmatic tool calling, and tool use examples.
Use cases
See Responsible AI for additional consideration for responsible use.Key use cases
- Coding: Opus 4.5 can confidently deliver multi-day software development projects in hours, working independently with the technical depth and taste to create efficient and straightforward solutions. It has improved performance across coding languages, with better planning and architecture choices—making it the ideal model for enterprise developers.
- Agents: Claude Opus 4.5, paired with our advanced tool use capabilities, enables more capable agents with new behaviors.
- Computer use: Our best computer-using model yet, Claude Opus 4.5 navigates new experiences with confident, consistent approaches that deliver more human-like browsing, enabling better web QA, workflow automation, and advanced user experiences.
- Enterprise workflows: Opus 4.5 can power agents that manage sprawling professional projects from start to finish. It better leverages memory to maintain context and consistency across files, alongside a step-change improvement in creating spreadsheets, slides, and docs.
- Financial analysis: Opus 4.5 connects the dots across complex information systems—regulatory filings, market reports, internal data—making sophisticated predictive modeling and proactive compliance possible.
- Cybersecurity: Opus 4.5 brings professional-grade analysis to security workflows, correlating logs, vulnerability databases, and threat intelligence for proactive threat detection and automated incident response.
Out of scope use cases
Please refer to the Claude Opus 4.5 system card .Pricing
Pricing is based on a number of factors. See pricing details here .Technical specs
Please refer to the Claude Opus 4.5 system card .Training cut-off date
September 2025Input formats
Image & text input: With powerful vision capabilities, Claude Opus 4.5 can process images and return text outputs to analyze and understand charts, graphs, technical diagrams, reports, and other visual assets. Text output: Claude Opus 4.5 can output text of a variety of types and formats, such as prose, lists, Markdown tables, JSON, HTML, code in various programming languages, and more.Supported language
Claude Opus 4.5 can understand and output a wide variety of languages, such as French, Standard Arabic, Mandarin Chinese, Japanese, Korean, Spanish, and Hindi. Performance will vary based on how well-resourced the language is.Supported Azure regions
GlobalSample JSON response
Success response:
200:
{
"content": [
{
"text": "Hi! My name is Claude.",
"type": "text"
}
],
"id": "msg_013Zva2CMHLNnXjNJJKqJ2EF",
"model": "claude-opus-4-5-20251101",
"role": "assistant",
"stop_reason": "end_turn",
"stop_sequence": null,
"type": "message",
"usage": {
"input_tokens": 31,
"cache_creation_input_tokens": 0,
"cache_read_input_tokens": 0,
"cache_creation": {
"ephemeral_5m_input_tokens": 0,
"ephemeral_1h_input_tokens": 0
},
"output_tokens": 25,
"service_tier": "standard"
}
}
Error response:
4XX:
{ "error": { "message": "Invalid request", "type": "invalid_request_error" }, "request_id": "", "type": "error" }
Model architecture
Please refer to the Claude Opus 4.5 system card .Long context
Claude Opus 4.5 has a 200K token context window.Optimizing model performance
Please refer to the Claude Opus 4.5 system card .Additional assets
- Claude Documentation : Visit Anthropic’s Claude documentation for a wealth of resources on model capabilities, prompting techniques, use case guidelines, and more.
- Extended Thinking Guide : Understand how best to use extended thinking with Claude.
- Claude Prompting Resources : Check out Anthropic's prompting tools and guides to learn how to craft prompts that elicit more helpful, nuanced responses.
- Claude Cookbooks : Check out example code for a variety of complex tasks, such as RAG from various web sources, making SQL queries, function calling, multimodal prompting, and more.
Distribution channels
- Claude API: For developers interested in building agents, Claude Opus 4.5 is available on the Claude Developer Platform.
- Claude Code: Use Claude Opus 4.5 with Anthropic’s industry-leading coding agent, Claude Code.
More information
Data handling
By default, we may process customer data in select countries in the US, Europe, Asia and Australia. We will only store data in data centers located in the United States. For more on data handling and retention, see our Privacy Center.By default, we will not use your inputs or outputs from our commercial products (Anthropic API and Claude Code Enterprise) to train our models. If you explicitly report feedback or bugs to us or otherwise choose to allow us to use your data, then we may use your chats and coding sessions to train our models.
To find out more information regarding your use of an Anthropic commercial offering, or if you would like to know how to contact us regarding a privacy related topic, see our Trust Center and Commercial Terms.
Responsible AI considerations
Safety techniques
The Claude Opus 4.5 system card describes in detail the wide range of evaluations Anthropic ran to assess the model’s safety and alignment.Safety evaluations
Claude Opus 4.5 represents incremental improvements over Claude Opus 4.1, with enhancements in reasoning quality, instruction-following, and overall performance. The Claude Opus 4.5 system card details comprehensive safety evaluations conducted in line with our Responsible Scaling Policy commitments. These include safeguards testing, agentic safety evaluations for computer use and coding capabilities, assessments of reward hacking behavior, Usage Policy compliance testing, alignment evaluations covering a range of misalignment risks, and model welfare assessments.Known limitations
Pleae refer to the Claude Opus 4.5 system card .Acceptable use
Acceptable use policy
Anthropic’s Usage Policy is intended to help our users stay safe and promote the responsible use of our products and services.Terms of Service
Terms of Service Link
Claude is a proprietary model developed by Anthropic. Usage is governed by Anthropic's Commercial Terms of Service for API access.Benchmarks
| Benchmark | Test Name | Score |
|---|---|---|
| Agentic coding | SWE-bench Verified | 80.9% |
| Agentic terminal coding | Terminal-bench 2.0 | 59.3% |
| Agentic tool use | τ2-bench | Retail: 88.9%, Telecom: 98.2% |
| Scaled tool use | MCP Atlas | 62.3% |
| Computer use | OSWorld | 66.3% |
| Novel problem solving | ARC-AGI-2 (Verified) | 37.6% |
| Graduate-level reasoning | GPQA Diamond | 87.0% |
| Visual reasoning | MMMU (validation) | 80.7% |
| Multilingual Q&A | MMMLU | 90.8% |
Benchmarking methodology
Please refer to the Claude Opus 4.5 system card .Public data summary
N/AModel Specifications
Context Length200000
Quality Index0.93
Training DataSeptember 2025
Last UpdatedNovember 2025
Input TypeText,Image,Code
Output TypeText
ProviderAnthropic
Languages8 Languages
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