What this error means
max_parallel_requests Current limit: N, Remaining: 0 is a LiteLLM failure pattern reported for developers trying to fix litellm max_parallel_requests counter not decrementing on cancelled streams. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.
Why this happens
Detailed root cause analysis in issue. Claude Code sends 2 HTTP POSTs per turn (speculative + confirmation), cancels POST A when POST B starts. CancelledError skips the decrement path. Counter grows by 1 per turn. Workaround provided (try/finally with async_log_failure_event).
Common causes
- LiteLLM's parallel request limiter has a counter leak when Claude Code's dual-POST pattern cancels mid-stream. Eventually all requests hit 429 Budget Exceeded. Affects production deployments using Claude Code through LiteLLM proxy.
- Detailed root cause analysis in issue. Claude Code sends 2 HTTP POSTs per turn (speculative + confirmation), cancels POST A when POST B starts. CancelledError skips the decrement path. Counter grows by 1 per turn. Workaround provided (try/finally with async_log_failure_event).
Quick fixes
- Confirm the exact error signature matches
max_parallel_requests Current limit: N, Remaining: 0. - 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.