Prompt Caching: Faster, Cheaper Multi-Turn AI

Prompt caching stores the processed form of a fixed prompt prefix — your system instructions, style guides, or a long reference document — so the model does not reprocess those tokens on every call. On the next request within the cache window, that prefix is a cache hit, which cuts latency and can drop input-token cost by up to 90%.

The rule is simple: keep the reusable content at the front and unchanging. Put your system prompt, tool definitions, and shared context first; place the variable user turn last. One edit inside the cached prefix invalidates it, so never interleave timestamps or per-request IDs into that block.

On CinderHub, prompt caching quietly powers multi-turn chat, storyboard iteration, and batch image or video prompts where the same creative brief repeats. Structure your prompts prefix-first, watch your cache-hit rate, and you get snappier responses on a smaller bill — no model downgrade required.