​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 soft 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)

• ​Welcome and Opening Remarks

• ​Intro to vLLM and Project Update

• ​Accelerating AI Inference with Speculative Decoding

• ​From Eval to Production: Building a Managed vLLM Service with llm-d

• ​Sardeenz - GPU Virtualization and Multi model deployment on single GPU. Hands-on Lab.

​​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.