# vllm-project/vllm

> A high-throughput and memory-efficient inference and serving engine for LLMs

- GitHub: https://github.com/vllm-project/vllm
- Website: https://vllm.ai
- Category: LLM & Inference (https://ideas.asveas.com/c/llm)
- Tags: amd, blackwell, cuda, deepseek, deepseek-v3, gpt, gpt-oss, inference, kimi, llama, llm, llm-serving, model-serving, moe
- Language: Python · License: Apache-2.0
- Stars: 96,755 · Forks: 24,689 · Open issues: 10,244
- Last push: 2026-11-11 (today)
- Vibe score: 96/100

## What it is
🔥 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. 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.

## When to use it
Reach for vllm when you need to call, serve, run locally, fine-tune or chat with a language model — it's written in Python and fits stacks tagged amd, blackwell, cuda, deepseek.

## Maintenance
vllm-project/vllm looks very actively maintained: the last push was today (2026-11-11), with 96,755 stars and 10,244 open issues.

## Quick start
```bash
git clone https://github.com/vllm-project/vllm.git
```

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Source: https://ideas.asveas.com/r/vllm-project/vllm · Catalog: https://ideas.asveas.com/llms.txt