LMCache Emerges as Open-Source Standard for LLM KV Cache Management, Surpassing 9,100 GitHub Stars

LMCache, an open-source KV cache management layer for LLM inference, surpasses 9,100 GitHub stars as it transforms temporary GPU cache into persistent, reusable knowledge—cutting time-to-first-token and boosting throughput across major hardware vendors like NVIDIA and AMD.

• LMCache is an open-source KV cache management layer for LLM inference that transforms KV cache from a temporary GPU state into persistent, reusable knowledge, significantly reducing time-to-first-token and improving throughput for long-context and agentic workloads.
• The project supports tiered KV cache offloading across CPU memory, local SSDs, and remote backends like Redis, S3, and NIXL, while offering production-level observability metrics, pluggable storage backends, and PD disaggregation for KV transfer across prefill and decode workers.
• LMCache is vendor-neutral, integrates with major serving engines and hardware vendors including NVIDIA and AMD, has surpassed 9,100 GitHub stars with 241 contributors, and is backed by the Tensormesh organization as it grows toward becoming the de-facto standard for KV cache management in LLM inference.