Model detail
Claude Opus 4.6
Opus 4.6 is Anthropic’s strongest model for coding and long-running professional tasks. It is built for agents that operate across entire workflows rather than single prompts, making it especially effective for large codebases, complex refactors, and multi-step debugging that unfolds over time. The model shows deeper contextual understanding, stronger problem decomposition, and greater reliability on hard engineering tasks than prior generations. Beyond coding, Opus 4.6 excels at sustained knowledge work. It produces near-production-ready documents, plans, and analyses in a single pass, and maintains coherence across very long outputs and extended sessions. This makes it a strong default for tasks that require persistence, judgment, and follow-through, such as technical design, migration planning, and end-to-end project execution. For users upgrading from earlier Opus versions, see our [official migration guide here](https://openrouter.ai/docs/guides/guides/model-migrations/claude-4-6-opus)
Model specs
- Model ID
-
claude-opus-4-6
- Context length
- 1M
- Max output
- 128K
- I/O modalities
- Released
- 2026-02
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API endpoints
One MixRoute gateway, OpenAI-compatible
-
Anthropic Messages
/v1/messagesPOST -
OpenAI-compatible
/v1/chat/completionsPOST -
Gemini
/v1beta/models/{model}:generateContentPOST
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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?
Coding and long-running professional tasks end-to-end
Use Opus 4.6 for large codebases, complex refactors, and multi-step debugging. It excels at sustained knowledge work, producing near-production-ready documents, plans, and analyses in a single pass.
What should you check before using it?
Test on hard engineering and knowledge work tasks
Opus 4.6 shows deeper contextual understanding and stronger problem decomposition. Test your most demanding engineering tasks and verify the quality of sustained knowledge work outputs. Knowledge cutoff: 2025-05.
Why use it through MixRoute?
Claude Opus 4.6 takes text and images on one route
Text and image inputs share the same route and the same key. MixRoute serves Claude Opus 4.6 on the OpenAI-compatible endpoint /v1/chat/completions; point your existing client at https://api.mixroute.ai/v1 with the model ID claude-opus-4-6 and re-run your integration tests.
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Capabilities & compatibility
Unconfirmed capabilities stay "Unknown," no guesses
Tool calling
Claude Opus 4.6 supports function and tool calls.
tools definition; the response returns tool_calls to execute and feed results back.
Structured output
Claude Opus 4.6 can produce JSON-formatted output on demand.
response_format: { type: "json_schema" } forces valid JSON output.
Streaming
Claude Opus 4.6 supports streamed responses.
stream: true streams tokens incrementally, so chat UIs render as they arrive.
Prompt caching
Claude Opus 4.6 supports prompt caching under supported routing conditions.
Vision input
Claude Opus 4.6 can process image inputs alongside text.
image_url content part alongside text messages.
OpenAI SDK
Call Claude Opus 4.6 through MixRoute's OpenAI-compatible endpoint.
base_url to https://api.mixroute.ai/v1; everything else follows the OpenAI style.
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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-4-6 supports up to 128000 output tokens per request. Plan your prompts to stay within this limit, and use the max_tokens or max_completion_tokens parameter to control output length.
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.