LLM caches: saving tokens without dropping quality

A caching proxy in front of a language model can cut the token bill significantly, but it introduces subtle risks if the design is not careful. Which cache types work in production, where the usual traps sit, and how to add them without degrading the experience.

November 29, 2025 6 min 234

Architecture

Inference routers: choosing a model based on the request

An inference router decides which model answers each incoming request, weighing cost, latency and how hard the request actually is. Well-built inference routers cut total token spend by 30 to 70 percent with no quality loss the user can perceive. Four patterns cover most cases: length, task type, an auxiliary classifier, and learned routing.

November 26, 2025 5 min 250 4.1