53d2ea3789
### What this PR does / why we need it?
maybe fixes
[#1728](https://github.com/vllm-project/vllm-ascend/issues/1728#issuecomment-3065083433)
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Test Qwen3-32B tp=4 with:
```bash
vllm serve --port 1234 Qwen/Qwen3-32B \
--served-model-name Qwen3-32B \
--tensor-parallel-size 4 \
--swap-space 16 \
--max-model-len 6000 \
--load-format dummy \
--disable-log-stats \
--disable-log-requests \
```
Request batch_size=128 input/output token=1024
**In 0.9.2rc1**
```text
=====================================================
Total TPS with prefill(tokens/s) : 785.1395
Total TPS without prefill : 846.6809
Mean TPS with prefill : 6.1339
Mean TPS without prefill : 6.6147
=====================================================
Mean TTFT(ms) : 10307.8123
Max TTFT(ms) : 21423.0733
Min TTFT(ms) : 362.3602
=====================================================
Mean TPOT(ms) : 151.3051
Max TPOT(ms) : 159.4649
Min TPOT(ms) : 140.899
=====================================================
Total Time(s) : 175.6032
Request Throughput(requests/s) : 0.7289
=====================================================
```
**Apply this PR**
```text
=====================================================
Total TPS with prefill(tokens/s) : 811.0014
Total TPS without prefill : 876.4423
Mean TPS with prefill : 6.3359
Mean TPS without prefill : 6.8472
=====================================================
Mean TTFT(ms) : 10263.8382
Max TTFT(ms) : 21151.2547
Min TTFT(ms) : 375.9136
=====================================================
Mean TPOT(ms) : 146.1686
Max TPOT(ms) : 154.0957
Min TPOT(ms) : 136.8879
=====================================================
Total Time(s) : 169.8579
Request Throughput(requests/s) : 0.7536
=====================================================
```
The TPOT performance gap between these two sets of data is about 3%.
- vLLM version: v0.9.2
- vLLM main:
8dfb45ca33
Signed-off-by: lianyibo <lianyibo1@kunlunit.com>
vLLM Ascend Plugin
| About Ascend | Documentation | #sig-ascend | Users Forum | Weekly Meeting |
English | 中文
Latest News 🔥
- [2025/06] User stories 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 page is now live! All contributions deserve to be recorded, thanks for all contributors.
- [2025/05] We've released first official version 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.
- [2025/03] We hosted the vLLM Beijing Meetup with vLLM team! Please find the meetup slides here.
- [2025/02] vLLM community officially created 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.
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, 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-Expert, Embedding, Multi-modal LLMs can run seamlessly on the Ascend NPU.
Prerequisites
- Hardware: Atlas 800I A2 Inference series, Atlas A2 Training series
- OS: Linux
- Software:
- Python >= 3.9, < 3.12
- CANN >= 8.1.RC1
- PyTorch >= 2.5.1, torch-npu >= 2.5.1.post1.dev20250619
- vLLM (the same version as vllm-ascend)
Getting Started
Please use the following recommended versions to get started quickly:
| Version | Release type | Doc |
|---|---|---|
| v0.9.2rc1 | Latest release candidate | QuickStart and Installation for more details |
| v0.7.3.post1 | Latest stable version | QuickStart and Installation for more details |
Contributing
See CONTRIBUTING for more details, which is a step-by-step guide to help you set up 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
- Please use User forum for usage questions and help.
Branch
vllm-ascend has main branch and dev branch.
- main: main branch，corresponds to the vLLM main branch, and is continuously monitored for quality through Ascend CI.
- vX.Y.Z-dev: development branch, created with part of new releases of vLLM. For example,
v0.7.3-devis the dev branch for vLLMv0.7.3version.
Below is maintained branches:
| Branch | Status | Note |
|---|---|---|
| main | Maintained | CI commitment for vLLM main branch and vLLM 0.9.x branch |
| v0.7.1-dev | Unmaintained | Only doc fixed is allowed |
| v0.7.3-dev | Maintained | CI commitment for vLLM 0.7.3 version, only bug fix is allowed and no new release tag any more. |
| v0.9.1-dev | Maintained | CI commitment for vLLM 0.9.1 version |
Please refer to Versioning policy 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)
License
Apache License 2.0, as found in the LICENSE file.