What this error means

[Bug]: Duplicate Usage Aggregation Across Billing Cycles — April 30th tokens double-counted in May, pre-exhausting balances is a LiteLLM failure pattern reported for developers trying to litellm proxy admin sees usage data from end-of-month incorrectly carried over into next month's total, causing 'month-to-date' counter not to reset, leading to premature budget exhaustion. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.

Why this happens

GitHub issue BerriAI/litellm#27917 (created 2026-05-14, just opened). Directly impacts billing: end-of-month tokens double-counted into next month, pre-exhausting team budgets. High commercial value: LiteLLM users are typically proxy operators managing multi-model budgets. Clear monetary impact drives strong search intent. Category: LiteLLM (exact match). Fresh issue with little competition.

Common causes

  • GitHub issue BerriAI/litellm#27917 (created 2026-05-14, just opened). Directly impacts billing: end-of-month tokens double-counted into next month, pre-exhausting team budgets. High commercial value: LiteLLM users are typically proxy operators managing multi-model budgets. Clear monetary impact drives strong search intent. Category: LiteLLM (exact match). Fresh issue with little competition.

Quick fixes

  1. Confirm the exact error signature matches [Bug]: Duplicate Usage Aggregation Across Billing Cycles — April 30th tokens double-counted in May, pre-exhausting balances.
  2. Check the LiteLLM account, local tool state, and provider configuration involved in the failing workflow.
  3. 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

  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.