How do you design multi-layer caching in LLM inference systems?

Multi-layer caching combines response caching, embedding cache, and retrieval cache to reduce latency and cost.

LLM systems use multiple caching layers: exact response cache (fastest), semantic cache (embedding similarity), and retrieval cache (vector search results). Each layer reduces redundant computation. Cache invalidation is managed using TTL, model versioning, and prompt versioning to avoid stale outputs.