😎Check out how LMCache excels in Multi-Turn Context Chat and RAG use cases in this brief video!

Want to create your own LLM Inference Endpoint on Any Cloud in seconds? . We're announcing the alpha release of LMIgnite, the one-click high-performance inference stack built for speed and scale. Powered by LMCache, vLLM, and vLLM Production Stack. 🤖 Join the alpha and

With RAG and agents becoming ubiquitous in LLM systems, tuning quality and performance JOINTLY is essential to achieve the best LLM quality-of-experience. Our paper at SOSP this year, addresses this exact tradeoff!🔥

The gang 🫡

𝗟𝗠𝗖𝗮𝗰𝗵𝗲 𝗿𝗲𝗮𝗰𝗵𝗲𝘀 𝟮,𝟬𝟬𝟬+ 𝘀𝘁𝗮𝗿𝘀 𝗼𝗻 𝗚𝗶𝘁𝗛𝘂𝗯! 🌟 . A huge thank you to our open-source community—your support is fueling next‑gen efficient LLM Inference!

🚀 𝗧𝗲𝗻𝗰𝗲𝗻𝘁 x 𝗟𝗠𝗖𝗮𝗰𝗵𝗲 Collaboration: Integrating 𝗠𝗼𝗼𝗻𝗰𝗮𝗸𝗲 Store for Enhanced LLM Inference Caching! 🥮🥮. Excited to share insights from a powerful collaboration between Tencent engineers and the LMCache Lab team! 🎉. With the help from Tencent Engineers,

Our open-source LLM cluster deployment solution is 10x faster than SOTA OSS solution. Check out the vLLM Production-Stack!🤩🤩🤩. Since Jan 2025, vLLM Production Stack has been the reference open-source vLLM inference cluster solution with advanced KV cache offloading and K8s

🚀 We're thrilled to announce vLLM Production Stack—an open-source, Enterprise-Grade LLM inference solution that is now an official first-party ecosystem project under vLLM!. Why does this matter?.A handful of companies focus on LLM training, but millions of apps and businesses