What this error means

Requests to the ChatCompletions_Create Operation under Azure OpenAI API version 2024-06-01 have exceeded token rate limit of your current OpenAI S0 pricing tier. Please retry after 86400 seconds. is a OpenAI API failure pattern reported for developers trying to resolve azure openai 429 rate limit error even when making requests well below stated rate limits on s0 pricing tier. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.

Why this happens

Microsoft Q&A question reporting Azure OpenAI 429 errors with an unusually long retry-after period (86400 seconds = 24h). Indicates per-resource-group or per-deployment token rate limits on S0 tier may be lower than expected. Affects enterprise users paying for Azure OpenAI credits.

Common causes

  • Microsoft Q&A question reporting Azure OpenAI 429 errors with an unusually long retry-after period (86400 seconds = 24h). Indicates per-resource-group or per-deployment token rate limits on S0 tier may be lower than expected. Affects enterprise users paying for Azure OpenAI credits.

Quick fixes

  1. Confirm the exact error signature matches Requests to the ChatCompletions_Create Operation under Azure OpenAI API version 2024-06-01 have exceeded token rate limit of your current OpenAI S0 pricing tier. Please retry after 86400 seconds..
  2. Check the OpenAI API 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.