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When you tell the model to explain its reasoning, the model responds with the steps that it employs to solve the problem Indicates whether to include thoughts in the response Going through this process can sometimes improve.
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You can set a lower token limit for less complex tasks, or a higher limit for more complex ones Positive values penalize tokens that repeatedly appear in the generated text, the full name of the model’s endpoint The following table shows the minimum and maximum amounts you can set the.
Description right now supports { groundingmetadata
Null }, need to set the new thinking_budget # tokens Just like for anthropic on google vertex. If you enable extended thinking, you must specify the number of tokens that the model can use for its internal reasoning as part of the output. I'm seeing the thought tokens exceed the thinking budget too with adk 1.5.0 when using gemini 2.5 flash
Description vertex now supports extraction of thinking tokens in certain gemini models I have opened a pr #6261 to provide a suggested implementation of this An error will be returned if this field is set for models that don't support thinking. The ability to manually set a thinking budget (up to 24,576 tokens, with a floor of 1,024 tokens) or disable thinking entirely (budget = 0) is documented in google cloud’s generative ai docs.
To start using the gemini api in vertex ai, create a google cloud account
After creating your account, use this document to review the gemini model request body, model.
