An artificial intelligence service rate limit controls usage over time. Limits can apply to requests per minute, tokens per minute, concurrent runs, daily quotas or other units, and they may vary by customer and model.
Applications should handle limits with queues, backoff, caching and alternative models where appropriate. A free service with strict or changing limits may be suitable for experiments but unreliable for production demand.
Acronyms and aliases
model API rate limit synonymAI service rate limit variantartificial intelligence service rate limit variant
Related terms
Frequently asked questions
Why do AI providers use rate limits?
Limits protect capacity, control abuse, manage fair access and align usage with service tiers or commercial plans.
How should an application handle model API rate limits?
Use bounded retries with backoff, queues, clear user feedback and tested fallback behavior when appropriate.
