Type: inference engine
vLLM is an open-source, high-throughput inference and serving engine for large language models, known for its PagedAttention memory management. It is widely used to deploy open-weight models efficiently in production. GROUNDING tracks vLLM’s releases, supported models, and role in self-hosted AI serving.
Recent Updates
- 2026-07-22: At WAIC, Taichu Yuanqi showed a heterogeneous compute platform built for agent-era workloads (量子位) · qbitai.com — Agents Tool Use 量子位 · QbitAI 太初（杭州）集成电路有限公司 太初元碁 华为 · 沐曦 阿里平头哥 国盛证券 · AMD 阿里云 河南空港智算中心 瑞莱智慧 安势信息 清源智契 典枢科技 数安信 龙芯 申威 飞腾 百度 · 清华大学 湖南大学 山东大学 东润 百度飞桨 · 上海人工智能实验室 量旋科技 允中 杨晋喆 苏姿丰 徐世真 Megatron-LM DeepSpeed PaddleHelix · PyTorch TecoQSim RiverONE AtomWorld · AlphaFold3 CrossDNA Intern-S1
FAQ
What is vLLM?
vLLM is an open-source, high-throughput inference and serving engine for large language models, known for its PagedAttention memory management. It is widely used to deploy open-weight models efficiently in production. GROUNDING tracks vLLM’s releases, supported models, and role in self-hosted AI serving.
What does this page track?
Dated radar mentions, source links, related concepts, and builder-relevant context for vLLM, collected automatically by GROUNDING.
When was vLLM last mentioned?
vLLM was most recently mentioned in a radar update dated 2026-07-22.
Category: Text / Language Models