A Claude API request returning HTTP 429 has usually hit a rate limit, but the correct response depends on the error body and rate-limit headers. Sending the same request immediately in a tight loop can make the problem worse. First distinguish a rate limit from an overloaded-service response, then pace traffic and retry only when appropriate.

Anthropic documents limits and error handling in its official Rate limits guide and Errors reference.

Quick checklist

  1. Record the status code and error type.
  2. Inspect rate-limit headers returned with the response.
  3. Reduce request bursts and concurrent calls.
  4. Respect any retry timing supplied by the API.
  5. Use bounded exponential backoff with jitter for retryable failures.
  6. Review account limits and usage before requesting an increase.

Identify the error type

Do not treat every failed request as a rate limit. Check the HTTP status, error type, response body, and headers. A 429 indicates rate limiting; an overloaded response is a different condition and may need a slower retry strategy. Authentication and validation errors need configuration changes, not repeated retries.

Log request IDs and timing for diagnosis, but never log your API key or sensitive prompt content.

Read the rate-limit headers

Anthropic exposes headers that help clients understand request and token limits, current utilization, and reset timing. Inspect the actual headers returned for your account and model rather than relying on fixed values copied from an example.

Different dimensions can constrain a request. A workload may be limited by request rate or token throughput, and a long prompt can consume more of the available budget than a short one. Review request size and traffic patterns together.

Retry with backoff

For retryable rate-limit or transient server errors, use exponential backoff and add jitter. If the response provides a retry-after or reset hint, respect it. Cap retries and stop when the retry budget is exhausted.

Do not retry client errors such as invalid requests or authentication failures without changing the request. Avoid stacking retry loops across SDK, application, and queue layers because they can accidentally multiply attempts.

Smooth traffic and reduce token demand

If multiple workers send requests simultaneously, use a queue or shared rate limiter. Limit concurrency and spread batch jobs over time. Remove unnecessary conversation history and duplicated context when possible, and request a focused output.

Measure both request volume and token consumption. A lower request count does not necessarily solve a token-throughput limit if each request is very large.

Review limits and usage

Check the current Anthropic Console limits and usage for your organization and model. If normal, paced traffic still consistently reaches the limit, review the options for a higher limit or contact Anthropic through official support. Do not assume that a higher model tier removes every constraint.

Backoff helps with temporary throttling, but it cannot fix an invalid key, malformed input, unsupported model, or exhausted account balance. A persistent 429 may mean the workload exceeds the configured quota and needs lower throughput or an approved limit increase. An overloaded error may instead reflect temporary service capacity.

Official sources: Anthropic API rate limits and API errors.

For broader AI troubleshooting, start with the exact error and the official documentation for the product involved. This article focuses on the specific API or publishing failure described above, rather than general introductory guidance.