Google speeds up AI responses with prefix caching

Google just rolled out prefix caching for its GKE Inference Gateway, a feature that stores repeated API responses so the same queries don't have to hit the model again. The result is faster responses and lower bills for whatever's calling the API.

What prefix caching actually does is simple: when your app makes the same request twice, the gateway serves the cached copy instead of sending it back through the full inference pipeline. It's the same trick your abuela uses — don't cook the same meal twice if you already got leftovers. For AI services that handle tons of repeated queries, this adds up fast.

The move lands right in the middle of an AI infrastructure arms race. AWS, Azure, and OpenAI are all chasing the same goal — make AI calls cheaper and faster for anyone paying by the token. Google's play is to make it easier for companies already running on GKE to optimize without rewriting their code.

Why this matters for us: every time Google cuts AI inference costs, it's one less thing keeping small shops and immigrant-run businesses from putting AI tools on their own terms.