LMCache: Open-Source Cache Layer Speeds Up Inference
JafarNajafov · x · 2026-07-17
LMCache is an open-source KV cache layer designed to store reusable text across GPU, CPU, disk, or even S3, making it reusable across any vLLM or SGLang instance.
- It goes beyond simple prefix caching, supporting the cross-node reuse of reusable text from any position within a prompt.
- When integrated with vLLM, the authors report achieving 3–10x lower TTFT on multi-turn QA and RAG workloads, while also significantly saving GPU compute cycles.
- It has already been adopted by Google Cloud, CoreWeave, GMI Cloud, Redis, Weka, and NVIDIA Dynamo.
- The project is licensed under Apache 2.0 and can be installed via pip install lmcache.
Related event: LMCache framed as a KV-cache layer for LLM inference(5 posts)→
More from Infra
- 12 KV Cache Reduction Techniques Every AI Engineer Should Understand, Explained — blaizedsouza · 2026-09-11
- The shadow GPU capacity market is formalizing, with Meta selling excess compute to outside buyers — DavidLinthicum · 2026-09-11
- Engram's random reads don't suit SSDs; CPU-memory over NVLink could serve all 72 GPUs — bookwormengr · 2026-09-11
- 80% of the DIY LLM inference hype posters have already quit — it's brutally hard systems work — abhijithneil · 2026-09-11
- Hugging Face's Ultra Scale Playbook: a free book on training LLMs on GPU clusters — mdancho84 · 2026-09-11
- Is inference latency becoming the biggest bottleneck for production AI agents? — Euphoric_Sea632 · 2026-09-11