vllm
by vllm-projectA high-throughput and memory-efficient inference and serving engine for LLMs
About vllm
vllm is a Python open-source ai skill project by vllm-project. A high-throughput and memory-efficient inference and serving engine for LLMs With 83,571 GitHub stars and 18,328forks, it's one of the AI Skill tools worth knowing. You can download the source, browse it on GitHub, or read the full setup guide in the README below.
From the project README
Easy, fast, and cheap LLM serving for everyone
| Documentation | Blog | Paper | Twitter/X | User Forum | Developer Slack |
🔥 We have built a vLLM website to help you get started with vLLM. Please visit vllm.ai to learn more. For events, please visit vllm.ai/events to join us.
About
vLLM is a fast and easy-to-use library for LLM inference and serving.
Originally developed in the Sky Computing Lab at UC Berkeley, vLLM has grown into one of the most active open-source AI projects built and maintained by a diverse community of many dozens of academic institutions and companies from over 2000 contributors.
vLLM is fast with:
- State-of-the-art serving throughput
- Efficient management of attention key and value memory with PagedAttention
This is an excerpt from the project's own README, quoted here for reference. Read the full README on GitHub →
vllm — FAQ
What is vllm?
A high-throughput and memory-efficient inference and serving engine for LLMs
Is vllm free to use?
Yes. vllm is open-source and free. You can browse the source on GitHub or download it here at no cost — no signup required.
How do I install and run vllm?
Download the latest source as a ZIP from GitHub (or clone the main branch), then follow the setup steps in the README below.
What language is vllm written in?
vllm is primarily written in Python.
How popular is vllm?
vllm has 83,571 stars and 18,328 forks on GitHub, and was last updated 6/22/2026 — a useful signal of how actively it's maintained and trusted by developers.