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Claude Opus 5 chat from Anthropic through an OpenAI-compatible endpoint. It takes up to 1,000,000 tokens of text and image context and returns up to 128,000, with low, medium or high reasoning effort, up to 128 tool definitions and SSE streaming.

Input $4.50Output $22.50per 1 million tokens10% below the publisher's list priceCached input $0.45Cache write $5.50Anthropic official priceInput $5Output $25

Workbench

These examples were written for this endpoint. Replace the prompt and sample media URLs with your own accessible inputs, then check the current quote and model availability before submitting.

  • Input types
    Text
    Output types
    Text
    Input
    $4.50 / 1 million tokens
    Cached input
    $0.45 / 1 million tokens
    Output
    $22.50 / 1 million tokens
    Context
    1M
    Max output
    128K

    $4.50/22.50per 1 million tokens · input / output

    persona-continuity

    Continuing a long exchange. History, persona and established limits all travel with the request, with no summarisation layer in between - that is what decides whether the character still remembers, thirty turns in, what it said.

    • 4096
  • Input types
    Text
    Output types
    Text
    Input
    $4.50 / 1 million tokens
    Cached input
    $0.45 / 1 million tokens
    Output
    $22.50 / 1 million tokens
    Context
    1M
    Max output
    128K

    $4.50/22.50per 1 million tokens · input / output

    long-running-refactor

    A change that spans several files with dependencies between the steps. What is tight here is not the output length but whether it remembers the decision it made first, so the whole context stays in the request.

    • 16000
    • high
  • Input types
    Text
    Output types
    Text
    Input
    $4.50 / 1 million tokens
    Cached input
    $0.45 / 1 million tokens
    Output
    $22.50 / 1 million tokens
    Context
    1M
    Max output
    128K

    $4.50/22.50per 1 million tokens · input / output

    spec-vs-implementation

    Specification and implementation in the same request, with the model left to find what does not line up. Effort at high, because missing a divergence costs more than a few extra seconds.

    • 8000
    • high

This example starts at Input $4.50 / Output $22.50 per 1 million tokens. The Playground updates the estimate when you change the settings.