_1722956449156001fz1R.png "Anyscale Logo")
The vLLM team will brief the past year of progress in "building the fastest and easiest-to-use open-source LLM inference and serving engine". We are excited to share major updates in terms of adoption, features, performance, community, and the governance of the project. We will then share the roadmap for the upcoming releases.
Ray Summit 2024
In-Person Agenda
The State of vLLM 2024
Speakers
vLLM @Berkeley, University of Chicago
PhD Student / vLLM Maintainer, UC Berkeley
- Tuesday, Oct 11:00 PM - 1:30 PM PDTYerba Buena Salon 10
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