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Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minuteStart with the HTTP status and structured error body, then check the relevant response headers and request context. A 400 or 401 usually needs a request or configuration fix; a 429 may mean temporary throttling or an account limit; and a timeout does not tell you whether the server received the request. Match the cause before retrying.
Identify the failure before changing your code
Use the status code as a clue, not a complete diagnosis. Read the response’s error details, including error.code when present, and compare them with the account or project context and the request you sent. OpenAI’s [Error codes guide](https://developers.openai.com/api/docs/guides/error-codes) describes these categories; its status and limit behavior may change, so check the live documentation when a response does not fit the patterns below.
| What you see | What to check | Next action |
|---|---|---|
400 |
Error body, required fields, parameter names and values | Correct the request shape or invalid parameter. Resending an unchanged request is unlikely to help. |
401 |
Key validity or revocation, organization and project selection, and any configured IP allowlist | Use an active credential with the right project context, and update the allowlist if applicable. Keep the key out of browser and app-side code. |
429 with a temporary rate-limit error |
Error type or code, Retry-After, request and token limit headers, concurrent callers, and recent traffic changes |
Reduce or pace traffic, then retry within a bounded time and attempt budget, honoring the server delay when supplied. |
429 with a credits, spend, or usage-limit error |
The specific error.code and the relevant billing, project, or organization context |
Address the applicable credit, billing, or limit setting. Retrying without an account change will not restore access. |
500 or 503 |
Error details, whether the issue persists, and Retry-After if present |
For a transient server-side issue, wait and retry cautiously. If it persists, check OpenAI service status and contact support with the request ID. |
| Timeout or connection error | Client deadline and cancellation, network, proxy, SSL certificate and firewall settings, and whether a response ID arrived | Separate a client-side connection or deadline problem from a server response. Keep a retry and end-to-end time budget, and use a unique client request ID to aid investigation. |
These mappings are diagnostic starting points, not universal guarantees: the error details and account context determine what a particular response means.
Handle 429 errors without making throttling worse
Distinguish throttling from an account limit
A 429 can indicate temporary rate limiting, but it can also indicate exhausted credits or a spend or usage limit. Check the error code and message before deciding to retry. For a billing or quota condition, take the account action indicated by the response rather than treating it as a short-lived traffic spike.
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Reduce and smooth request volume
Rate limits can apply to both requests and tokens. Inspect the relevant limit, remaining, and reset headers for requests and tokens; project-token headers may also be applicable. Reduce unnecessary calls and concurrency, pace work rather than sending bursts, and ramp traffic gradually. OpenAI’s [Rate limits guide](https://developers.openai.com/api/docs/guides/rate-limits) notes that slow_down can occur when traffic rises too quickly even if ordinary requests-per-minute and tokens-per-minute limits are not exhausted. Its ramping advice is operational guidance, not a fixed threshold or general industry statistic.
Retry only errors that can recover
For an eligible transient error, follow this order:
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- If the response includes a valid
Retry-After, wait at least that long. Treat it as a minimum, not permission to retry sooner. - Add a small random delay to reduce the chance that multiple clients retry together.
- If the header is absent or unusable, use exponential backoff with jitter.
- Set both a maximum number of attempts and a total time budget. If a valid server delay exceeds your configured maximum, defer the operation instead of retrying early.
- Check your installed OpenAI SDK version and retry configuration. Avoid stacking an unbounded application retry loop on top of SDK retries.
Repeated failed calls can still contribute to per-minute limits, so a rapid retry loop may deepen the problem. A slow_down response calls for smoother traffic and a gradual ramp, not merely a short pause followed by the same burst. OpenAI’s [Rate limits guide](https://developers.openai.com/api/docs/guides/rate-limits) covers rate-limit behavior; the [Error codes guide](https://developers.openai.com/api/docs/guides/error-codes) describes errors that require a request or account change instead.
For streaming requests, distinguish an HTTP error returned before the stream begins from an error event received after streaming has started. If the client has already consumed output, do not blindly replay the request: consider duplicate work and any application side effects first.
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Diagnose timeouts and connection failures separately
A timeout means the client stopped waiting; by itself, it does not establish whether OpenAI received or processed the request. A retry could therefore repeat work. Record client-side timing, cancellation, and deadline behavior, and use an end-to-end retry budget rather than assuming no response means no server-side processing.
For a connection failure, check network settings, proxy configuration, SSL certificates, and firewall rules. If a timeout or network problem prevented receipt of the response’s x-request-id, OpenAI’s [API reference](https://developers.openai.com/api/reference/overview) says a unique X-Client-Request-Id can help support look up whether the request arrived and when. Follow the reference’s ASCII and length constraints for that value.
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Log diagnostic evidence without exposing credentials
OpenAI recommends logging the server-generated x-request-id in production deployments to make support investigations more efficient, according to its [API reference](https://developers.openai.com/api/reference/overview). Keep it with the status, error code, client-observed timing, and retry outcome so you can connect a failure to a specific attempt.
When available, capture openai-processing-ms and the request and token limit, remaining, and reset headers. Compare server processing time with total client-observed time to help separate service processing from time spent in the caller’s network and application. Never log or expose the API key as ordinary diagnostic metadata; do not place it in browser or app-side code.
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Reduce perceived latency without confusing it with recovery
Streaming can show users output sooner, and chunking can reduce the time needed to process work. These techniques address waiting time, not the cause of a failed request: they do not fix invalid credentials, request errors, exhausted quota, rate limits, connectivity faults, or server errors. For latency design, see OpenAI’s [Latency optimization guide](https://developers.openai.com/api/docs/guides/latency-optimization).
Status and rate-limit behavior can vary by model, project, account, and platform conditions. The OpenAI documentation linked above was checked on October 3, 2026; consult the live pages for current details rather than assuming a fixed limit applies to every API user.
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