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Why are AI provider errors different? Because an HTTP status code describes only part of a failure: different causes can share the same status, and providers expose different details and recovery signals. How should you handle AI API errors across providers? Keep each provider’s original error data, add a stable application-level category, and make retry decisions from the cause and available timing guidance—not the status number alone.
Why an HTTP status code is not a diagnosis
HTTP status is useful for identifying a broad class of response, but it does not tell your application whether to wait, slow down, fix a request, or change account settings. Even within one provider, a status can cover conditions with different remedies. Across providers, the same status may carry different provider-specific meanings.
For example, OpenAI documents 429 responses for both rate limiting and account usage or spend limits. A 429 `rate_limit_error` with `slow_down` may indicate that traffic increased too quickly; the remedy is to reduce pressure and retry later. A usage or spend limit requires an account-level correction, not another retry. OpenAI separately documents 503 `service_unavailable_error` with `server_is_overloaded` for model overload. Its guidance says a `slow_down` response can occur even when published requests-per-minute and tokens-per-minute limits have not been exceeded. OpenAI rate-limit guidance and its error-code reference describe these distinctions.
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Preserve the provider’s error, then add your own category
Normalize for application policy without flattening away the evidence needed to debug a failure or revise your mapping later. Store a common record alongside the unmodified provider response wherever practical.
providerandoperationhttp_statusprovider_error_typeandprovider_error_codemessageandrequest_id, when suppliedretry_after, when supplied, with its original value or representationattemptand a normalizedcategory
Possible categories include invalid_request, authentication_or_permission, rate_limited, quota_or_billing, overloaded, transient_provider_failure, and unknown_provider_error. These are application design choices, not a shared provider standard. Keep the raw fields so that a new provider code can be mapped without losing its original meaning.
The need to retain provider-specific details is concrete: Anthropic documents 529 overloaded_error, while Google Gemini documents a structured API error object and status categories including 400, 401, 429, and 503. Preserve those details rather than reducing either response to a number. See the Anthropic API error guide and Gemini API error reference.
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| Provider | Documented examples | Retry guidance and SDK behavior | What the application should distinguish |
|---|---|---|---|
| OpenAI | 429 can represent rate limiting or account usage/spend limits. A 429 rate_limit_error with slow_down indicates a traffic-pacing problem; 503 service_unavailable_error with server_is_overloaded indicates overload. |
Follow Retry-After when present; otherwise increase delay and add a small random delay. Official SDKs automatically retry eligible 429 and 503 responses. |
Separate traffic pressure from account limits; retries do not fix billing, spend, or quota errors. A slow_down signal can occur below documented rate limits. |
| Anthropic | Documented examples include 500 api_error and 529 overloaded_error. |
The official SDK retries transient failures such as connection errors, rate limits, and 5xx server errors with exponential backoff, twice by default, and honors retry-after when present. |
Map 529 overload to an application-level transient overload category while retaining the original status and error code. |
| Google Gemini | The API error reference describes a structured error object for standard non-streaming requests and categories including 400, 401, 429, and 503. | Official Gemini SDKs include default exponential-backoff retry logic for transient timeouts, network issues, and 429/5xx responses. | Retain the structured error details. The cited guidance does not establish that retry metadata is carried in the same place across providers. |
Provider contracts and SDK behavior can change. Consult the OpenAI error-code guide, OpenAI rate-limit guide, Anthropic error guide, Gemini troubleshooting guide, and Gemini errors reference for the current details relevant to your API and SDK.
Build a retry decision path around the remedy
- Fix request and configuration errors before retrying. Treat malformed requests as non-retryable until the request is corrected. Authentication or permission failures require a credential or access correction. Repeating an unchanged request does not address either cause.
- Separate account limits from traffic limits. A quota, billing, spend, or usage restriction needs account-level action. A traffic rate limit may clear when request pressure is reduced and enough time has passed. Do not classify every 429 as the same kind of retryable failure.
- Retry only plausibly transient failures. Network interruptions, overload, and server failures may clear with time or reduced pressure. Honor provider timing instructions such as
Retry-Afterwhen present. Otherwise, use bounded exponential backoff with jitter where appropriate. - Set an overall budget. Limit attempts or elapsed time so retries cannot continue indefinitely. Make exhaustion visible to the calling code or operator with the normalized category and preserved provider details.
- Return an actionable outcome. Tell a caller or operator whether to correct the request, repair credentials, reduce traffic, wait, or address account configuration. Avoid presenting a transient retry as the remedy for a persistent account problem.
Account for SDK retries before adding application retries
Official SDKs already retry some transient failures, and their policies are not identical. OpenAI says its official SDKs automatically retry eligible 429 and 503 responses. Anthropic says its SDK retries transient failures with exponential backoff, twice by default, and honors retry-after when available. Google says its official Gemini SDKs retry transient timeouts, network issues, and 429/5xx responses with exponential backoff by default.
If your application also retries, understand the SDK’s behavior for the exact language and version you deploy. Otherwise, one logical operation can trigger multiple layers of attempts, increasing latency and request pressure. Choose where the retry budget lives, or coordinate the layers so their combined behavior stays bounded.
Keep provider fallback separate from error normalization
A common error category can help decide what to do, but it does not make replaying a request against another provider automatically safe. The documented guidance here does not establish cross-provider guarantees for request replay, billing consequences, streaming interruption recovery, or semantic equivalence between models. Treat fallback as a separate application decision: verify the operation’s replay safety and define acceptable differences before routing a failed call elsewhere.
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Streaming failures also need provider- and operation-specific handling. The cited error guidance does not establish that streaming interruptions have the same semantics or expose retry metadata in the same way as standard non-streaming responses. Do not infer parity from a shared HTTP status or a normalized category.
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