LMCache is a KV cache management layer for LLM inference. It turns KV cache from a temporary state into reusable AI-native knowledge that can be stored persistently, reused across multiple serving engines, monitored with an observability stack, and transformed for better generation quality. As a result, LMCache reduces TTFT (time-to-first-token) and improves throughput , especially for long-context agentic, multi-turn conversation, and knowledge-augmented workloads (e.g., RAG).

LMCache is becoming an integral layer in the LLM inference ecosystem , with community -driven integration with serving engines, inference frameworks, hardware vendors, storage systems, and infrastructure providers.