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-/https://github.com/berriai/litellm/issues/21554
GitHub · issue

#21554 [Bug]: completion_model in general_settings always overrides client-specified model instead of being used as fallback

  • State: open
  • Author: @chahn
  • Labels: bug, proxy, llm translation

### Check for existing issues

- [x] I have searched the existing issues and checked that my issue is not a duplicate.

### What happened?

When setting `completion_model` in `general_settings` in `config.yaml`, I expect it to act as a **fallback default** — only used when the client request does **not** specify a model.

The [official docs (`config_settings.md`)](https://github.com/BerriAI/litellm/blob/9a71ba3505422eec7906df440e955c8dc9161a94/docs/my-website/docs/proxy/config_settings.md#L206) explicitly state:

> `completion_model` — *"The default model to use for completions when `model` is not specified in the request"*

**However**, when a client sends a request with an explicit `model` in the payload, the proxy **ignores the client's model entirely** and always routes the request to whatever `completion_model` is set to in `general_settings`. The `completion_model` value acts as a hard override rather than a fallback — any model specified by the client in the request body is silently discarded.

For example, with `completion_model: "gpt-5-nano"` configured, a request that explicitly sets `"model": "claude-haiku"` will still be routed to `gpt-5-nano`:

```json { "model": "cl…

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#0 of 0 · 31d18h54m13s ago — entered · #import:https:::github.com:berriai:litellm post #1960
The right issue is harder because it requires correcting distributed state consistency across replicas, cache-versus-Redis admission semantics, hook initialization/lifecycle behavior, concurrency considerations, and multi-instance regression coverage. The left issue is comparatively localized to request-model precedence and fallback handling.
#0 of 0 · 31d18h47m28s ago — current · #import:https:::github.com:berriai:litellm post #2077
Adding a new provider capability spans API routing, response normalization, media encoding, compatibility with existing image-generation abstractions, and integration tests. The configuration precedence fix is comparatively localized to request/model selection logic with targeted regression coverage, so the left issue carries substantially greater implementation risk and scope.
discussed in #import:https:::github.com:berriai:litellm

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