API Rate Limits and Cost Optimisation

Developers frequently conflate two distinct constraints, and treating them as the same thing leads to debugging in the wrong place. Rate limits are throughput constraints: they govern how fast you can consume an API, typically expressed as tokens per minute, requests per minute, or tokens per day. When you exceed a rate limit, the API responds with an HTTP 429 status code, defined as too many requests; the server is not saying your account is out of funds, it is saying you are sending traffic faster than your tier permits. Spend quotas are volume or budget caps, which may appear as a monthly token ceiling or a hard spend limit in your billing console. Exhausting a quota surfaces differently per provider: some return a distinct account-level error, while others reuse HTTP 429 with a specific error code such as insufficient_quota, so read the error body rather than the status code alone; either way, it is not resolved by slowing your request rate. You can hit a rate limit with budget to spare, and you can exhaust a quota while sending requests well within your per-minute limit, so diagnosing which problem you have is the first step to fixing it. Why do rate limits exist? The short answer is fairness. LLM inference is GPU-bound, and a single large, sustained workload can starve other users sharing the same infrastructure, so rate limits ensure fair allocation across thousands of concurrent tenants and protect overall system stability. Higher-tier plans carry higher limits because the provider has planned for that capacity; the limit is a ceiling on how fast you may send, not a guaranteed level of throughput. Think of it like motorway smart lanes, where variable speed limits keep finite road capacity flowing for everyone. The standard way to handle 429 errors is exponential backoff with jitter. When a 429 is received, wait before retrying, and increase the wait time with each successive failure. Adding randomness, the jitter, to the delay prevents a thundering herd: if every client retries at the same interval, they all hit the API simultaneously and trigger another 429. Most provider SDKs include built-in retry logic, so verify it is enabled before writing your own.