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Rate Limits and Quotas

Understand request, concurrency, and token limits and handle 429 with queues and backoff.

Limits protect platform and account stability. Values can vary by account, model, and service plan; use the limits displayed in the console.

Common limit dimensions

DimensionMeaningClient response
Request rateRequests allowed per time window.Token buckets, leaky buckets, or queue shaping.
ConcurrencySimultaneous in-flight requests.Semaphores and separate pools for long and short work.
Token rateInput/output tokens processed per time window.Trim context, cap output, and spread work over time.
Balance / budgetAvailable account spending or internal budget.Alert before exhaustion interrupts service.

Handling 429

  1. Stop immediate retries and read any available limit information in the response.
  2. Use exponential backoff, for example roughly 1, 2, then 4 seconds, with random jitter.
  3. Bound retry attempts and total waiting time.
  4. Reduce global concurrency or use a bounded queue rather than letting every task retry independently.
  5. For persistent limits, analyze peak traffic and request an appropriate quota.

Rate-limit response contract

Header names and values require platform confirmation. Published guidance must specify whether RPM, TPM, and concurrency apply to accounts, projects, API keys, or models and provide readable response headers.

InformationDocumentation requirement
Limits and remaining capacityHeader names for request, token, and concurrency limits and remaining quota.
Reset timeWindow algorithm, time zone, precision, and whether reset values are seconds or timestamps.
Retry-AfterWhether it is returned and whether to parse seconds or an HTTP date.
429 error objectStable error types distinguishing request, token, concurrency, account-quota, and platform-capacity limits.
Quota increasesRequired business data, review time, temporary capacity, and service-level options.

Quota planning

  • Estimate concurrency from average request duration, not RPM alone.
  • Reserve capacity for releases, campaigns, and batch workloads.
  • Separate online interaction and offline work into different queues and priorities.
  • Apply per-tenant limits to prevent noisy neighbors.
  • Provide peak concurrency, token distributions, target models, and business time windows when requesting capacity.