
Austin vLLM & llm-d AI Inference Meetup
Texas vLLM & llm-d Inference Meetup Hosted by Red Hat AI, NVIDIA, and the AITX Community, this event takes place on July 16, 2026 in Austin, Texas. Join us for
Texas vLLM & llm-d Inference Meetup Hosted by Red Hat AI, NVIDIA, and the AITX Community, this event takes place on July 16, 2026 in Austin, Texas. Join us for a deep dive into the engine room of vLLM and llm-d AI inferencing, where we will focus on the architecture, optimizations, and raw engineering required to run inference at scale. Whether you’re looking to squeeze every last token out of your GPU cluster or you're curious about the latest commits to the vLLM and llm-d ecosystems, this is the room you want to be in. What to Expect Deep Technical Sessions: Hear directly from the maintainers and core committers of vLLM and llm-d Scale in Production: Learn from industry leaders about deploying LLMs in production Live Demos: See live demos focused on real-world workflows Networking: Stick around for food and drinks. It’s a great chance to chat with the speakers and exchange ideas with fellow developers and engineers. Who Should Attend vLLM and llm-d users and contributors ML and infra engineers working on inference and serving Platform teams running GenAI in production Anyone curious about efficient inference across local, cloud, and Kubernetes Agenda (Subject to More Awesomeness) 5:00PM – 5:30PM — Doors Open, Check-In 5:30PM – 5:40PM — Welcome and Opening Remarks 5:40PM – 6:10PM — Intro to vLLM and Project Update 6:10PM – 6:30PM — Intro to Scalable, Distributed Inference with Kubernetes and llm-d 6:30PM – 6:50PM — From Single Calls to Long Workflows 6:50PM – 7:30PM — Hands-on Workshop: Getting Started with Accurate Model Compression and Benchmarking 7:30PM – 8:00PM — Discussion and Q&A 8:00PM – 9:00PM — Networking, Food and Drinks Important information Registration closes 24 hours before the event. We cannot admit unregistered attendees. Please bring a photo ID to verify your registration on arrival. See you in Austin If you are building, deploying, or scaling inference, this is the room to be in. See you soon!
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