Token Kiosk
Models

Provider notes

Per-provider and per-model quirks to be aware of.

These are documented behaviors that differ from the generic OpenAI request shape.

Kimi (kimi/kimi-k2.6)

kimi-k2.6 ignores temperature, top_p, and penalty parameters.

MiniMax

MiniMax models ignore presence_penalty and frequency_penalty parameters.

Bedrock — kimi-k2-thinking

bedrock/kimi-k2-thinking is a reasoning model that uses an internal thinking budget. Use max_tokens ≥ 1000 to ensure output is produced.

Bedrock — gpt-oss-20b

bedrock/gpt-oss-20b requires max_tokens ≥ 500 to produce output. Accepts reasoning_effort.

Azure — gpt-5.x

azure/gpt-5.5 and azure/gpt-5.6-sol are reasoning models. The gateway translates max_tokens to Azure's max_completion_tokens for you, but temperature, top_p, penalty params, and logprobs are silently dropped — only default sampling is supported.

thinking and reasoning_effort are model-specific

These are not gateway-wide flags, and the gateway does not reject them with an error. Support is per-model:

  • bedrock/claude-* accepts thinking; reasoning content comes back as a reasoning field (see Anthropic (Claude) models).
  • bedrock/gpt-oss-* and azure/gpt-5.* accept reasoning_effort.
  • azure/gpt-5.* silently drops thinking if sent.
  • Every other provider forwards these fields as-is to its upstream API, which may ignore or error on them depending on that provider's own request validation.

Omit both fields unless you're targeting one of the reasoning models above.

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