Introduction on Serving Vllm On Agentic Production Workloads Inferact Ray Summit 2026
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Serving LLMs for Agents at Scale with Ray + vLLM | JPMorgan Chase | Ray Summit 2026
Serving vLLM on Intel GPUs, CPUs, and Gaudi | Intel | Ray Summit 2026
🎙️Simon Mo CEO of @inferact: 5 new VLLM features in 2026!
PyTorch loves vLLM | Meta | Ray Summit 2026
AMD and vLLM: What's New | AMD | Ray Summit 2026
Inside VLLM: Production Best Practices, Model Integration and Road Map - Kaichao You, Inferact
Serving a Frontier Open Model with Ray & vLLM | Nscale | Ray Summit 2026
Building an AI Science Factory | Andrew Beam (Lila Sciences) | Ray Summit 2026
Scaling DSpark Training Using vLLM, Speculators and Mooncake | Red Hat | Ray Summit 2026
Lightning on Agentic: Embedded LLM, Anyscale, Novita, and Verda | Ray Summit 2026
LLM Post-Training and High-Performance Serving | Anyscale | Ray Summit 2026
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Last Updated: October 3, 2026
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Summary
Large language models demand significant computational power for inference, and TPUs are becoming a first-class target for ... Don't miss out! Join us at our next KubeCon + CloudNativeCon event in Salt Lake City, United States (Nov 9–12, A simpler setup delivered more tokens per second, with the first token arriving sooner for a single request, than the model card's ... Only about 5% of scientific hypotheses can be verified cheaply. The rest require real experiments, which makes most of science ... State-of-the-art speculative decoding lives or dies on the drafter, and training drafters well at scale is a Four focused lightning talks explore systems work for "Github repository: github.com/anyscale/
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