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  <picture>
    <source media="(prefers-color-scheme: dark)" srcset="https://raw.githubusercontent.com/vllm-project/vllm-ascend/main/docs/source/logos/vllm-ascend-logo-text-dark.png">
    <img alt="vllm-ascend" src="https://raw.githubusercontent.com/vllm-project/vllm-ascend/main/docs/source/logos/vllm-ascend-logo-text-light.png" width=55%>
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<h3 align="center">
vLLM Ascend Plugin
</h3>

<div align="center">

[![DeepWiki](https://img.shields.io/badge/DeepWiki-Ask_AI-_.svg?style=flat&color=0052D9&labelColor=000000&logo=data:image/png;base64, )](https://deepwiki.com/vllm-project/vllm-ascend)

</div>

<p align="center">
| <a href="https://www.hiascend.com/en/"><b>About Ascend</b></a> | <a href="https://docs.vllm.ai/projects/ascend/en/latest/"><b>Documentation</b></a> | <a href="https://slack.vllm.ai"><b>#SIG-Ascend</b></a> | <a href="https://discuss.vllm.ai/c/hardware-support/vllm-ascend-support"><b>Users Forum</b></a> | <a href="https://tinyurl.com/vllm-ascend-meeting"><b>Weekly Meeting</b></a> |
</p>

<p align="center">
<a ><b>English</b></a> | <a href="README.zh.md"><b>中文</b></a>
</p>

---
*Latest News* 🔥

- [2026/02] We released the new official version [v0.13.0](https://github.com/vllm-project/vllm-ascend/releases/tag/v0.13.0)! Please follow the [official guide](https://docs.vllm.ai/projects/ascend/en/v0.13.0/) to start using vLLM Ascend Plugin on Ascend.
- [2025/12] We released the new official version [v0.11.0](https://github.com/vllm-project/vllm-ascend/releases/tag/v0.11.0)! Please follow the [official guide](https://docs.vllm.ai/projects/ascend/en/v0.11.0/) to start using vLLM Ascend Plugin on Ascend.
- [2025/09] We released the new official version [v0.9.1](https://github.com/vllm-project/vllm-ascend/releases/tag/v0.9.1)! Please follow the [official guide](https://docs.vllm.ai/projects/ascend/en/v0.9.1/tutorials/large_scale_ep.html) to start deploying large-scale Expert Parallelism (EP) on Ascend.
- [2025/08] We hosted the [vLLM Beijing Meetup](https://mp.weixin.qq.com/s/7n8OYNrCC_I9SJaybHA_-Q) with vLLM and Tencent! Please find the meetup slides [here](https://drive.google.com/drive/folders/1Pid6NSFLU43DZRi0EaTcPgXsAzDvbBqF).
- [2025/06] [User stories](https://docs.vllm.ai/projects/ascend/en/latest/community/user_stories/index.html) page is now live! It kicks off with LLaMA-Factory/verl/TRL/GPUStack to demonstrate how vLLM Ascend‌ assists Ascend users in enhancing their experience across fine-tuning, evaluation, reinforcement learning (RL), and deployment scenarios.
- [2025/06] [Contributors](https://docs.vllm.ai/projects/ascend/en/latest/community/contributors.html) page is now live! All contributions deserve to be recorded, thanks for all contributors.
- [2025/05] We've released the first official version [v0.7.3](https://github.com/vllm-project/vllm-ascend/releases/tag/v0.7.3)! We collaborated with the vLLM community to publish a blog post sharing our practice: [Introducing vLLM Hardware Plugin, Best Practice from Ascend NPU](https://blog.vllm.ai/2025/05/12/hardware-plugin.html).
- [2025/03] We hosted the [vLLM Beijing Meetup](https://mp.weixin.qq.com/s/VtxO9WXa5fC-mKqlxNUJUQ) with vLLM team! Please find the meetup slides [here](https://drive.google.com/drive/folders/1Pid6NSFLU43DZRi0EaTcPgXsAzDvbBqF).
- [2025/02] vLLM community officially created [vllm-project/vllm-ascend](https://github.com/vllm-project/vllm-ascend) repo for running vLLM seamlessly on the Ascend NPU.
- [2024/12] We are working with the vLLM community to support [[RFC]: Hardware pluggable](https://github.com/vllm-project/vllm/issues/11162).

---

## Overview

vLLM Ascend (`vllm-ascend`) is a community maintained hardware plugin for running vLLM seamlessly on the Ascend NPU.

It is the recommended approach for supporting the Ascend backend within the vLLM community. It adheres to the principles outlined in the [[RFC]: Hardware pluggable](https://github.com/vllm-project/vllm/issues/11162), providing a hardware-pluggable interface that decouples the integration of the Ascend NPU with vLLM.

By using vLLM Ascend plugin, popular open-source models, including Transformer-like, Mixture-of-Experts (MoE), Embedding, Multi-modal LLMs can run seamlessly on the Ascend NPU.

## Prerequisites

- Hardware: Atlas 800I A2 Inference series, Atlas A2 Training series, Atlas 800I A3 Inference series, Atlas A3 Training series, Atlas 300I Duo (Experimental)
- OS: Linux
- Software:
    - Python >= 3.10, < 3.12
    - CANN == 8.5.0 (Ascend HDK version refers to [here](https://www.hiascend.com/document/detail/zh/canncommercial/83RC2/releasenote/releasenote_0000.html))
    - PyTorch == 2.9.0, torch-npu == 2.9.0
    - vLLM (the same version as vllm-ascend)

## Getting Started

Please use the following recommended versions to get started quickly:

| Version    | Release type | Doc                                  |
|------------|--------------|--------------------------------------|
| v0.14.0rc1 | Latest release candidate | See [QuickStart](https://docs.vllm.ai/projects/ascend/en/latest/quick_start.html) and [Installation](https://docs.vllm.ai/projects/ascend/en/latest/installation.html) for more details |
| v0.13.0 | Latest stable version | See [QuickStart](https://docs.vllm.ai/projects/ascend/en/v0.13.0/quick_start.html) and [Installation](https://docs.vllm.ai/projects/ascend/en/v0.13.0/installation.html) for more details |

## Contributing

See [CONTRIBUTING](https://docs.vllm.ai/projects/ascend/en/latest/developer_guide/contribution/index.html) for more details, which is a step-by-step guide to help you set up the development environment, build and test.

We welcome and value any contributions and collaborations:

- Please let us know if you encounter a bug by [filing an issue](https://github.com/vllm-project/vllm-ascend/issues)
- Please use [User forum](https://discuss.vllm.ai/c/hardware-support/vllm-ascend-support) for usage questions and help.

## Branch

vllm-ascend has a main branch and a dev branch.

- **main**: main branch, corresponds to the vLLM main branch, and is continuously monitored for quality through Ascend CI.
- **releases/vX.Y.Z**: development branch, created alongside new releases of vLLM. For example, `releases/v0.13.0` is the dev branch for vLLM `v0.13.0` version.

Below are the maintained branches:

| Branch     | Status       | Note                                 |
|------------|--------------|--------------------------------------|
| main       | Maintained   | CI commitment for vLLM main branch and vLLM v0.13.0 tag   |
| v0.7.1-dev | Unmaintained | Only doc fixes are allowed |
| v0.7.3-dev | Maintained   | CI commitment for vLLM 0.7.3 version, only bug fixes are allowed, and no new release tags anymore. |
| v0.9.1-dev | Maintained   | CI commitment for vLLM 0.9.1 version |
| v0.11.0-dev | Maintained | CI commitment for vLLM 0.11.0 version |
| releases/v0.13.0 | Maintained | CI commitment for vLLM 0.13.0 version |
| rfc/feature-name | Maintained | [Feature branches](https://docs.vllm.ai/projects/ascend/en/latest/community/versioning_policy.html#feature-branches) for collaboration |

Please refer to [Versioning policy](https://docs.vllm.ai/projects/ascend/en/latest/community/versioning_policy.html) for more details.

## Weekly Meeting

- vLLM Ascend Weekly Meeting: <https://tinyurl.com/vllm-ascend-meeting>
- Wednesday, 15:00 - 16:00 (UTC+8, [Convert to your timezone](https://dateful.com/convert/gmt8?t=15))

## License

Apache License 2.0, as found in the [LICENSE](./LICENSE) file.
