LMIgnite: Fastest LLM Inference for Conversational and Long-Document AI, Only One Click Away
TL;DR: LLMs are transforming every product and service—from chatbots and copilots to intelligent document search and enterprise workflows. But running LLMs in production is still painfully slow, prohibitively expensive, and complex to manage. That changes today. We’re excited to announce the launch of LMIgnite — the first one-click deployable high-performance LLM inference backend for Conversational […]
Speeding Up LLM Inference: Beyond the Inference Engine
TL;DR: LLMs are rapidly becoming the dominant workload in enterprise AI. As more applications rely on real-time generation, inference performance — measured in speed, cost, and reliability — becomes the key bottleneck. Today, the industry focuses primarily on speeding up inference engines like vLLM, SGLang, and TensorRT. But in doing so, we’re overlooking a much […]
LLM Production Stack Goes Cross-Hardware: Ascend, Arm, and AMD Support Incoming
TL;DR: Our LLM Production Stack project just hit another milestone. We’re integrating with more hardware accelerators — including Ascend, Arm, and AMD — signaling growing maturity and broader applicability across enterprise and research settings. 🚀 LMCache Is Gaining Traction LMCache has quietly become the unsung hero in the LLM inference world. As a core component […]
Open-Source LLM Inference Cluster Performing 10x FASTER than SOTA OSS Solution
A picture is worth a thousand words: Executive Summary: [vLLM Production Stack Github] | [Get In Touch] | [Slack] | [Linkedin] | [Twitter] Benchmark setups Methods: Workload: Inspired by our production deployments, we create workloads that emulate a typical chat-bot document analysis workload. By default, each LLM query input has 9K tokens, including a document […]
AGI Infra for All: vLLM Production Stack as the Standard for Scalable vLLM Serving
TL;DR Why vLLM Production Stack? AGI isn’t just about better models–it is also about better systems to serve the models to the wide public so that everyone will have access to the new capabilities! In order to fully harness the power of Generative AI, every organization that take this AI revolution seriously needs to have […]
Deploying LLMs in Clusters #2: running “vLLM production-stack” on AWS EKS and GCP GKE
TL;DR [Github Link] | [More Tutorials] | [Get In Touch] AWS Tutorial (click here) GKE Tutorial (click here) The Context vLLM has taken the open-source community by storm, with unparalleled hardware and model support plus an active ecosystem of top-notch contributors. But until now, vLLM has mostly focused on single-node deployments. vLLM Production-stack is an […]
Deploying LLMs in Clusters #1: running “vLLM production-stack” on a cloud VM
TL;DR [Github Link] | [More Tutorials] | [Interest Form] Tutorial Video (click below) The Context vLLM has taken the open-source community by storm, with unparalleled hardware and model support plus an active ecosystem of top-notch contributors. But until now, vLLM has mostly focused on single-node deployments. vLLM Production-stack is an open-source reference implementation of an […]
High Performance and Easy Deployment of vLLM in K8S with “vLLM production-stack”
TL;DR The Context In the AI arms race, it’s no longer just about who has the best model—it’s about who has the best LLM serving system. vLLM has taken the open-source community by storm, with unparalleled hardware and model support plus an active ecosystem of top-notch contributors. But until now, vLLM has mostly focused on […]
