Claude API 400: thinking.type.enabled is not supported for this model

Claude returns 400 saying thinking.type.enabled is not supported? Newer models removed extended thinking. Use adaptive thinking and output_config.effort.

Reviewed October 25, 2026

What it means in plain English

Anthropic's Claude API errors page says Claude 4.7 and later models have removed extended thinking. Sending thinking: {"type": "enabled"} to any of these models returns a 400 invalid_request_error:

"thinking.type.enabled" is not supported for this model. Use "thinking.type.adaptive" and "output_config.effort" to control thinking behavior.

The reverse also happens. Models that support only extended thinking, Claude 4.5 and earlier, reject thinking: {"type": "adaptive"} with:

adaptive thinking is not supported on this model

So the thinking setting has to match the model you call.

Likely causes

  • You changed the model name to a newer Claude model, but the request still sends thinking: {"type": "enabled", "budget_tokens": N}.
  • You moved to an older model, but the request sends thinking: {"type": "adaptive"}.
  • A library or template sets the thinking field for you.

How to fix it, step by step

  1. Find the request that sets the thinking field, and note which model it calls.
  2. On Claude 4.7 and later models, replace thinking: {"type": "enabled"} with adaptive thinking. Anthropic says to use adaptive thinking, with output_config.effort to control how much thinking happens. Anthropic also says that if you omit the thinking parameter, the request runs with adaptive thinking.
  3. On Claude 4.5 and earlier models, use thinking: {"type": "enabled", "budget_tokens": N} instead of adaptive.
  4. Some newer models also reject thinking: {"type": "disabled"}. If you get a 400 that names thinking.type.disabled, read the message: Anthropic's errors page lists the setting each model accepts instead.
  5. Redeploy and send a test request.

How to check it worked

  • The request returns a normal response instead of a 400 invalid_request_error.
  • The thinking setting matches the model, so switching models does not bring the error back.

Sources

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