Model detail
claude-opus-5
Claude Opus 5 is Anthropic’s flagship model for demanding reasoning, coding, and long-horizon agentic work. It is particularly strong at end-to-end software tasks, code review and bug finding, visual analysis of charts and documents, complex office deliverables, and coordinating parallel subagents. The model maintains strong instruction following and tool use across extended tasks, while remaining effective at lower effort settings for workloads that prioritize latency and token efficiency.
Model specs
- Context length
- 1M
- Max output
- 128K
- I/O modalities
- Text / Image
- Released
- 2026-07
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API endpoints
One MixRoute gateway, OpenAI-compatible
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Anthropic Messages
/v1/messagesPOST -
OpenAI-compatible
/v1/chat/completionsPOST
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Pricing
Flat rate, unit: /1M Tokens
Input
$5.0000 /1M Tokens
Completion
$25.0000 /1M Tokens
Cache read
$0.5000 /1M Tokens
Cache creation
$6.2500 /1M Tokens
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Selection summary
Quickly judge whether it fits your workload
What is this model good for?
Demanding reasoning, coding, and long-horizon agentic work
Use Claude Opus 5 for end-to-end software tasks, code review, bug finding, visual analysis of charts and documents, complex office deliverables, and coordinating parallel subagents. It maintains strong instruction following and tool use across extended tasks.
What should you check before using it?
Tune reasoning effort for your latency and cost needs
Claude Opus 5 remains effective at lower effort settings for workloads prioritizing latency and token efficiency. Test your agentic workflows at different effort levels to find the right balance for your use case.
Why use it through MixRoute?
Use the compatible endpoint with stable model ID
Use the confirmed compatible endpoint with model ID claude-opus-5 through MixRoute, then run the same integration tests used for the current client.
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Token cost estimator
Live estimate from this page's pricing, not an actual bill
Share of the same prefix read repeatedly, up to 100%
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FAQ
Claude Opus 5 is Anthropic’s flagship model for demanding reasoning, coding, and long-horizon agentic work. It is particularly strong at end-to-end software tasks, code review and bug finding, visual analysis of charts and documents, complex office deliverables, and coordinating parallel subagents.
One endpoint, a testable decision
Test this model and alternate routes with the same request format
Start from a real workload, then let quality, total cost, and failure conditions decide whether to send production traffic.