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

  1. 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.
  2. Check the LiteLLM account, local tool state, and provider configuration involved in the failing workflow.
  3. 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

  1. Capture the exact error message and the command, editor action, or request that triggered it.
  2. Check whether the failure is account/auth, quota/rate, model/provider, local runtime, or deployment configuration.
  3. Review the source evidence below and compare it with your environment.
  4. Apply one change at a time and rerun the smallest failing action.
  5. 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.