#Specifying reasoning params

10 messages · Page 1 of 1 (latest)

velvet frigate
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Hi, I have some questions regarding reasoning params.
Is there any point of using o3-mini-high, if I specify the reasoning effort myself?

How can I find out the max supported values for reasoning max_tokens?
How do I even know if a given model supports reasoning or not?

For example here is r1:

{
  "id": "deepseek/deepseek-r1",
  "name": "DeepSeek: R1",
  "created": 1737381095,
  "description": "DeepSeek R1 is here: Performance on par with [OpenAI o1](/openai/o1), but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active in an inference pass.\n\nFully open-source model & [technical report](https://api-docs.deepseek.com/news/news250120).\n\nMIT licensed: Distill & commercialize freely!",
  "context_length": 65536,
  "architecture": {
    "modality": "text->text",
    "tokenizer": "DeepSeek",
    "instruct_type": "deepseek-r1"
  },
  "pricing": {
    "prompt": "0.00000055",
    "completion": "0.00000219",
    "image": "0",
    "request": "0",
    "input_cache_read": "0",
    "input_cache_write": "0",
    "web_search": "0",
    "internal_reasoning": "0"
  },
  "top_provider": {
    "context_length": 65536,
    "max_completion_tokens": 8192,
    "is_moderated": false
  },
  "per_request_limits": null
}
velvet frigate
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Anyone on this?

wide thicket
velvet frigate
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Clear! But is there any information at all in the models API which tells me if a model supports reasoning or not? I couldn't find anything.

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It'd be great to have the following information:

  • supports_reasoning true/false
  • supported_reasoning_levels: ['low','mid','high', '_max_tokens']
    or something similar
wide thicket
wide thicket
velvet frigate
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  • Gemini Thinking, o1, o3
wide thicket
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I forgot about those

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5 models, then