Kamya Shah

TL;DR: LLM API costs scale linearly with request volume. Applications with repeated or semantically similar queries pay for inference on every call, even when responses would be effectively identical. Semantic caching at the gateway intercepts requests before they reach a provider and returns a cached response for queries close

TL;DR: Every LLM provider caps requests and tokens per minute (RPM and TPM). Crossing a cap returns a 429 error that halts the request, and in production these become a top source of failed requests and stalled agent runs.Managing LLM traffic means handling two things at once: provider

Bifrost, Kong, Cloudflare, LiteLLM and OpenRouter compared on budget model, rate limits, alerts and deployment.