Sooo smol

Goblin is lowkey invading open-source projects lol.

massage and then cut, cruel

So glad to see our project --- LMCache --- is included in the discussion!

Free yes, only in April no

Key trick: don't use existing interactions directly ---- try to generate "lessons" from previous interactions instead.

LLM providers start to take control...

My time being spent: before using claude code --> write code after using claude code --> read code, understand and find potential issues My mental effort is not getting much lighter lol.

I want stardew valley on my IDE 😝

Heard that Qwen close-sourced their best model 😈

LLM for reranking helps you push Terminal Bench Sota by so much!

Latest models use efficient attentions like Mamba or sliding window. This gives huge potential in KV cache offloading layer --- LMCache needs to catch up.

Lol benchmaxxing, sooo true

Two years ago, we just have 2 NVIDIA A40. Two years later, our project is mentioned in Jensen Huang's GTC talk. Hope is the first-order weapon for human to fight for the future.

Why not store KV cache permanently? In case you missed it, #IBM recently posted two blogs for 𝗹𝗹𝗺-𝗱 𝗞𝟴𝗦 𝗟𝗠𝗖𝗮𝗰𝗵𝗲-based KV storage. Thrilled to keep building together. Avoiding recomputation is the goal, but it’s still rare to see KV cache treated as shared, persistent infrastructure in real production deployments. Excited to see LMCache be part of this with IBM, a long-time collaborator of the LMCache community. Thrilled to keep building together. These two posts are a great look at what that can actually look like in practice: 1. Rethinking LLM Inference Economics with llm-d, LMCache, and IBM Storage Scale community.ibm.com/community/… 2. Deploying Distributed LLM Inference Service with IBM Storage Scale for KV Cache Offloading community.ibm.com/community/… Great read for anyone interested in fast yet cheap LLM inference. #LMCache #vLLM #Kubernetes #K8s #KVCache

Physical LLM is on the way lol

🔴 Live from #GTC2026 On the floor with our Chief Scientist @this_will_echo and CTO #Yihua Chang — #KVCache is the hottest topic of the day. Even Jensen opened with it. 🎙️They covered topics like: #CacheBlend, @lmcache 0.4.0. and the super cool collab with @nvidia around a bot called #reachy using LMCache under the hood for 20x speedup #GTC2026 #KVCache #LMCache #TensorMesh

By offloading KV caches to SSD, we managed to reduce the time-to-first-token for @gmi_cloud without ANY extra infra cost!

🚀 LMCache has officially been out for 1.5 years now! Within its success, LMCache has become the default KV-cache library for open-source LLM inference (CPU offload, P2P sharing, multi-backend storage, vLLM/SGLang integration, and more). As a PyTorch Foundation Ecosystem project, LMCache is now used by enterprise leaders across the industry (GKE, AWS, Nvidia's Dynamo, llm-d…). 🤔What’s the secret to our product?? 🔎 Come see yourself: arxiv.org/pdf/2510.09665 ♥️ A huge thank you to our contributors and community, you’ve influenced what makes LMCache today. (@lmcache) #KVCache #LMCache #LLM #vLLM

Github is not acting normal... Our LMCache logo suddenly disappeared today, we didn't make any change. And we cannot even clone the repo using ssh. Github bad bad.