What this error means
litellm_rate_limit errors emitted as vendor_rate_limit — dashboards/callbacks attribute router-side throttles to upstream vendor instead of LiteLLM proxy is a LiteLLM failure pattern reported for developers trying to fix litellm rate-limit error categorization where router-side rpm/tpm throttling triggers (deployment-level and model-level) are falsely reported as vendor/third-party rate limits. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.
Why this happens
PR #27708 on BerriAI/litellm (open PR, created 2026-05-12, 4 comments). This is a follow-up to unified rate-limit error work (#27687). 9 router-side raises across lowest_tpm_rpm_v2.py and model_rate_limit_check.py emit wrong category. Impacts dashboards, callbacks, and alerting for enterprises routing traffic through LiteLLM proxy.
Common causes
- PR #27708 on BerriAI/litellm (open PR, created 2026-05-12, 4 comments). This is a follow-up to unified rate-limit error work (#27687). 9 router-side raises across lowest_tpm_rpm_v2.py and model_rate_limit_check.py emit wrong category. Impacts dashboards, callbacks, and alerting for enterprises routing traffic through LiteLLM proxy.
Quick fixes
- Confirm the exact error signature matches
litellm_rate_limit errors emitted as vendor_rate_limit — dashboards/callbacks attribute router-side throttles to upstream vendor instead of LiteLLM proxy. - Check the LiteLLM account, local tool state, and provider configuration involved in the failing workflow.
- Reduce request pressure, check quota or plan limits, and retry with backoff instead of immediate repeated requests.
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.