What this error means
model_info cost override (input_cost_per_token/output_cost_per_token) ignored when using litellm_proxy/ prefix is a LiteLLM failure pattern reported for developers trying to fix litellm model_info cost_per_token override being ignored when calling upstream litellm proxy. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.
Why this happens
GitHub issue 27656 (2026-05-11) reports that when a LiteLLM proxy (Y) calls another LiteLLM proxy (X) using litellm_proxy/ model prefix, cost overrides in model_info (input_cost_per_token, output_cost_per_token) are completely ignored. Upstream proxy costs are always used, breaking cost tracking for multi-layer proxy deployments.
Common causes
- When chaining LiteLLM proxy instances (Y calls X via litellm_proxy/ prefix), setting input_cost_per_token: 0 or output_cost_per_token: 0 in model_info has no effect. The upstream proxy's costs are always used instead. This breaks cost tracking accuracy for organizations running multi-layer LiteLLM proxy setups, making budget monitoring unreliable.
- GitHub issue 27656 (2026-05-11) reports that when a LiteLLM proxy (Y) calls another LiteLLM proxy (X) using litellm_proxy/ model prefix, cost overrides in model_info (input_cost_per_token, output_cost_per_token) are completely ignored. Upstream proxy costs are always used, breaking cost tracking for multi-layer proxy deployments.
Quick fixes
- Confirm the exact error signature matches
model_info cost override (input_cost_per_token/output_cost_per_token) ignored when using litellm_proxy/ prefix. - Check the LiteLLM account, local tool state, and provider configuration involved in the failing workflow.
- Compare the failing environment with a known working setup, then change one configuration value at a time.
Platform/tool-specific checks
- Verify the command, editor, extension, or API client that produced the error.
- Compare local settings with CI, deployment, or editor-level settings when the error appears in only one environment.
- Avoid deleting credentials, local model data, or project settings until the failing scope is clear.
Step-by-step troubleshooting
- Capture the exact error message and the command, editor action, or request that triggered it.
- Check whether the failure is account/auth, quota/rate, model/provider, local runtime, or deployment configuration.
- Review the source evidence below and compare it with your environment.
- Apply one change at a time and rerun the smallest failing action.
- Keep the working fix documented for the team or deployment environment.
How to prevent it
- Keep provider/tool configuration documented.
- Record non-secret diagnostics such as tool version, provider name, model name, and command path.
- Add a lightweight check before CI or production workflows depend on the tool.