Release note

Release note#

v0.9.2rc1 - 2025.07.11#

This is the 1st release candidate of v0.9.2 for vLLM Ascend. Please follow the official doc to get started. From this release, V1 engine will be enabled by default, there is no need to set VLLM_USE_V1=1 any more. And this release is the last version to support V0 engine, V0 code will be clean up in the future.

Highlights#

  • Pooling model works with V1 engine now. You can take a try with Qwen3 embedding model #1359.

  • The performance on Atlas 300I series has been improved. #1591

  • aclgraph mode works with Moe models now. Currently, only Qwen3 Moe is well tested. #1381

Core#

  • Ascend PyTorch adapter (torch_npu) has been upgraded to 2.5.1.post1.dev20250619. Don’t forget to update it in your environment. #1347

  • The GatherV3 error has been fixed with aclgraph mode. #1416

  • W8A8 quantization works on Atlas 300I series now. #1560

  • Fix the accuracy problem with deploy models with parallel parameters. #1678

  • The pre-built wheel package now requires lower version of glibc. Users can use it by pip install vllm-ascend directly. #1582

Other#

  • Official doc has been updated for better read experience. For example, more deployment tutorials are added, user/developer docs are updated. More guide will coming soon.

  • Fix accuracy problem for deepseek V3/R1 models with torchair graph in long sequence predictions. #1331

  • A new env variable VLLM_ENABLE_FUSED_EXPERTS_ALLGATHER_EP has been added. It enables the fused allgather-experts kernel for Deepseek V3/R1 models. The default value is 0. #1335

  • A new env variable VLLM_ASCEND_ENABLE_TOPK_TOPP_OPTIMIZATION has been added to improve the performance of topk-topp sampling. The default value is 0, we’ll consider to enable it by default in the future#1732

  • A batch of bugs have been fixed for Data Parallelism case #1273 #1322 #1275 #1478

  • The DeepSeek performance has been improved. #1194 #1395 #1380

  • Ascend scheduler works with prefix cache now. #1446

  • DeepSeek now works with prefix cache now. #1498

  • Support prompt logprobs to recover ceval accuracy in V1 #1483

v0.9.1rc1 - 2025.06.22#

This is the 1st release candidate of v0.9.1 for vLLM Ascend. Please follow the official doc to get started.

Highlights#

  • Atlas 300I series is experimental supported in this release. #1333 After careful consideration, this feature will NOT be included in v0.9.1-dev branch taking into account the v0.9.1 release quality and the feature rapid iteration to improve performance on Atlas 300I series. We will improve this from 0.9.2rc1 and later.

  • Support EAGLE-3 for speculative decoding. #1032

Core#

  • Ascend PyTorch adapter (torch_npu) has been upgraded to 2.5.1.post1.dev20250528. Don’t forget to update it in your environment. #1235

  • Support Atlas 300I series container image. You can get it from quay.io

  • Fix token-wise padding mechanism to make multi-card graph mode work. #1300

  • Upgrade vllm to 0.9.1 [#1165]https://github.com/vllm-project/vllm-ascend/pull/1165

Other Improvements#

  • Initial support Chunked Prefill for MLA. #1172

  • An example of best practices to run DeepSeek with ETP has been added. #1101

  • Performance improvements for DeepSeek using the TorchAir graph. #1098, #1131

  • Supports the speculative decoding feature with AscendScheduler. #943

  • Improve VocabParallelEmbedding custom op performance. It will be enabled in the next release. #796

  • Fixed a device discovery and setup bug when running vLLM Ascend on Ray #884

  • DeepSeek with MC2 (Merged Compute and Communication) now works properly. #1268

  • Fixed log2phy NoneType bug with static EPLB feature. #1186

  • Improved performance for DeepSeek with DBO enabled. #997, #1135

  • Refactoring AscendFusedMoE #1229

  • Add initial user stories page (include LLaMA-Factory/TRL/verl/MindIE Turbo/GPUStack) #1224

  • Add unit test framework #1201

Known Issues#

  • In some cases, the vLLM process may crash with a GatherV3 error when aclgraph is enabled. We are working on this issue and will fix it in the next release. #1038

  • Prefix cache feature does not work with the Ascend Scheduler but without chunked prefill enabled. This will be fixed in the next release. #1350

Full Changelog#

https://github.com/vllm-project/vllm-ascend/compare/v0.9.0rc2…v0.9.1rc1

v0.9.0rc2 - 2025.06.10#

This release contains some quick fixes for v0.9.0rc1. Please use this release instead of v0.9.0rc1.

Highlights#

  • Fix the import error when vllm-ascend is installed without editable way. #1152

v0.9.0rc1 - 2025.06.09#

This is the 1st release candidate of v0.9.0 for vllm-ascend. Please follow the official doc to start the journey. From this release, V1 Engine is recommended to use. The code of V0 Engine is frozen and will not be maintained any more. Please set environment VLLM_USE_V1=1 to enable V1 Engine.

Highlights#

  • DeepSeek works with graph mode now. Follow the official doc to take a try. #789

  • Qwen series models works with graph mode now. It works by default with V1 Engine. Please note that in this release, only Qwen series models are well tested with graph mode. We’ll make it stable and generalize in the next release. If you hit any issues, please feel free to open an issue on GitHub and fallback to eager mode temporarily by set enforce_eager=True when initializing the model.

Core#

  • The performance of multi-step scheduler has been improved. Thanks for the contribution from China Merchants Bank. #814

  • LoRA、Multi-LoRA And Dynamic Serving is supported for V1 Engine now. Thanks for the contribution from China Merchants Bank. #893

  • Prefix cache and chunked prefill feature works now #782 #844

  • Spec decode and MTP features work with V1 Engine now. #874 #890

  • DP feature works with DeepSeek now. #1012

  • Input embedding feature works with V0 Engine now. #916

  • Sleep mode feature works with V1 Engine now. #1084

Model#

  • Qwen2.5 VL works with V1 Engine now. #736

  • LLama4 works now. #740

  • A new kind of DeepSeek model called dual-batch overlap(DBO) is added. Please set VLLM_ASCEND_ENABLE_DBO=1 to use it. #941

Other#

Known Issue#

  • In some case, vLLM process may be crashed with aclgraph enabled. We’re working this issue and it’ll be fixed in the next release.

  • Multi node data-parallel doesn’t work with this release. This is a known issue in vllm and has been fixed on main branch. #18981

v0.7.3.post1 - 2025.05.29#

This is the first post release of 0.7.3. Please follow the official doc to start the journey. It includes the following changes:

Highlights#

  • Qwen3 and Qwen3MOE is supported now. The performance and accuracy of Qwen3 is well tested. You can try it now. Mindie Turbo is recomanded to improve the performance of Qwen3. #903 #915

  • Added a new performance guide. The guide aims to help users to improve vllm-ascend performance on system level. It includes OS configuration, library optimization, deploy guide and so on. #878 Doc Link

Bug Fix#

  • Qwen2.5-VL works for RLHF scenarios now. #928

  • Users can launch the model from online weights now. e.g. from huggingface or modelscope directly #858 #918

  • The meaningless log info UserWorkspaceSize0 has been cleaned. #911

  • The log level for Failed to import vllm_ascend_C has been changed to warning instead of error. #956

  • DeepSeek MLA now works with chunked prefill in V1 Engine. Please note that V1 engine in 0.7.3 is just expermential and only for test usage. #849 #936

Docs#

  • The benchmark doc is updated for Qwen2.5 and Qwen2.5-VL #792

  • Add the note to clear that only “modelscope<1.23.0” works with 0.7.3. #954

v0.7.3 - 2025.05.08#

🎉 Hello, World!

We are excited to announce the release of 0.7.3 for vllm-ascend. This is the first official release. The functionality, performance, and stability of this release are fully tested and verified. We encourage you to try it out and provide feedback. We’ll post bug fix versions in the future if needed. Please follow the official doc to start the journey.

Highlights#

  • This release includes all features landed in the previous release candidates (v0.7.1rc1, v0.7.3rc1, v0.7.3rc2). And all the features are fully tested and verified. Visit the official doc the get the detail feature and model support matrix.

  • Upgrade CANN to 8.1.RC1 to enable chunked prefill and automatic prefix caching features. You can now enable them now.

  • Upgrade PyTorch to 2.5.1. vLLM Ascend no longer relies on the dev version of torch-npu now. Now users don’t need to install the torch-npu by hand. The 2.5.1 version of torch-npu will be installed automatically. #662

  • Integrate MindIE Turbo into vLLM Ascend to improve DeepSeek V3/R1, Qwen 2 series performance. #708

Core#

  • LoRA、Multi-LoRA And Dynamic Serving is supported now. The performance will be improved in the next release. Please follow the official doc for more usage information. Thanks for the contribution from China Merchants Bank. #700

Model#

  • The performance of Qwen2 vl and Qwen2.5 vl is improved. #702

  • The performance of apply_penalties and topKtopP ops are improved. #525

Other#

  • Fixed a issue that may lead CPU memory leak. #691 #712

  • A new environment SOC_VERSION is added. If you hit any soc detection error when building with custom ops enabled, please set SOC_VERSION to a suitable value. #606

  • openEuler container image supported with v0.7.3-openeuler tag. #665

  • Prefix cache feature works on V1 engine now. #559

v0.8.5rc1 - 2025.05.06#

This is the 1st release candidate of v0.8.5 for vllm-ascend. Please follow the official doc to start the journey. Now you can enable V1 egnine by setting the environment variable VLLM_USE_V1=1, see the feature support status of vLLM Ascend in here.

Highlights#

  • Upgrade CANN version to 8.1.RC1 to support chunked prefill and automatic prefix caching (--enable_prefix_caching) when V1 is enabled #747

  • Optimize Qwen2 VL and Qwen 2.5 VL #701

  • Improve Deepseek V3 eager mode and graph mode performance, now you can use –additional_config={‘enable_graph_mode’: True} to enable graph mode. #598 #719

Core#

  • Upgrade vLLM to 0.8.5.post1 #715

  • Fix early return in CustomDeepseekV2MoE.forward during profile_run #682

  • Adapts for new quant model generated by modelslim #719

  • Initial support on P2P Disaggregated Prefill based on llm_datadist #694

  • Use /vllm-workspace as code path and include .git in container image to fix issue when start vllm under /workspace #726

  • Optimize NPU memory usage to make DeepSeek R1 W8A8 32K model len work. #728

  • Fix PYTHON_INCLUDE_PATH typo in setup.py #762

Other#

  • Add Qwen3-0.6B test #717

  • Add nightly CI #668

  • Add accuracy test report #542

v0.8.4rc2 - 2025.04.29#

This is the second release candidate of v0.8.4 for vllm-ascend. Please follow the official doc to start the journey. Some experimental features are included in this version, such as W8A8 quantization and EP/DP support. We’ll make them stable enough in the next release.

Highlights#

  • Qwen3 and Qwen3MOE is supported now. Please follow the official doc to run the quick demo. #709

  • Ascend W8A8 quantization method is supported now. Please take the official doc for example. Any feedback is welcome. #580

  • DeepSeek V3/R1 works with DP, TP and MTP now. Please note that it’s still in experimental status. Let us know if you hit any problem. #429 #585 #626 #636 #671

Core#

  • ACLGraph feature is supported with V1 engine now. It’s disabled by default because this feature rely on CANN 8.1 release. We’ll make it available by default in the next release #426

  • Upgrade PyTorch to 2.5.1. vLLM Ascend no longer relies on the dev version of torch-npu now. Now users don’t need to install the torch-npu by hand. The 2.5.1 version of torch-npu will be installed automatically. #661

Other#

  • MiniCPM model works now. #645

  • openEuler container image supported with v0.8.4-openeuler tag and customs Ops build is enabled by default for openEuler OS. #689

  • Fix ModuleNotFoundError bug to make Lora work #600

  • Add “Using EvalScope evaluation” doc #611

  • Add a VLLM_VERSION environment to make vLLM version configurable to help developer set correct vLLM version if the code of vLLM is changed by hand locally. #651

v0.8.4rc1 - 2025.04.18#

This is the first release candidate of v0.8.4 for vllm-ascend. Please follow the official doc to start the journey. From this version, vllm-ascend will follow the newest version of vllm and release every two weeks. For example, if vllm releases v0.8.5 in the next two weeks, vllm-ascend will release v0.8.5rc1 instead of v0.8.4rc2. Please find the detail from the official documentation.

Highlights#

  • vLLM V1 engine experimental support is included in this version. You can visit official guide to get more detail. By default, vLLM will fallback to V0 if V1 doesn’t work, please set VLLM_USE_V1=1 environment if you want to use V1 forcely.

  • LoRA、Multi-LoRA And Dynamic Serving is supported now. The performance will be improved in the next release. Please follow the official doc for more usage information. Thanks for the contribution from China Merchants Bank. #521.

  • Sleep Mode feature is supported. Currently it’s only work on V0 engine. V1 engine support will come soon. #513

Core#

  • The Ascend scheduler is added for V1 engine. This scheduler is more affinity with Ascend hardware. More scheduler policy will be added in the future. #543

  • Disaggregated Prefill feature is supported. Currently only 1P1D works. NPND is under design by vllm team. vllm-ascend will support it once it’s ready from vLLM. Follow the official guide to use. #432

  • Spec decode feature works now. Currently it’s only work on V0 engine. V1 engine support will come soon. #500

  • Structured output feature works now on V1 Engine. Currently it only supports xgrammar backend while using guidance backend may get some errors. #555

Other#

  • A new communicator pyhccl is added. It’s used for call CANN HCCL library directly instead of using torch.distribute. More usage of it will be added in the next release #503

  • The custom ops build is enabled by default. You should install the packages like gcc, cmake first to build vllm-ascend from source. Set COMPILE_CUSTOM_KERNELS=0 environment to disable the compilation if you don’t need it. #466

  • The custom op rotay embedding is enabled by default now to improve the performance. #555

v0.7.3rc2 - 2025.03.29#

This is 2nd release candidate of v0.7.3 for vllm-ascend. Please follow the official doc to start the journey.

  • Quickstart with container: https://vllm-ascend.readthedocs.io/en/v0.7.3-dev/quick_start.html

  • Installation: https://vllm-ascend.readthedocs.io/en/v0.7.3-dev/installation.html

Highlights#

  • Add Ascend Custom Ops framewrok. Developers now can write customs ops using AscendC. An example ops rotary_embedding is added. More tutorials will come soon. The Custom Ops compilation is disabled by default when installing vllm-ascend. Set COMPILE_CUSTOM_KERNELS=1 to enable it. #371

  • V1 engine is basic supported in this release. The full support will be done in 0.8.X release. If you hit any issue or have any requirement of V1 engine. Please tell us here. #376

  • Prefix cache feature works now. You can set enable_prefix_caching=True to enable it. #282

Core#

  • Bump torch_npu version to dev20250320.3 to improve accuracy to fix !!! output problem. #406

Model#

  • The performance of Qwen2-vl is improved by optimizing patch embedding (Conv3D). #398

Other#

  • Fixed a bug to make sure multi step scheduler feature work. #349

  • Fixed a bug to make prefix cache feature works with correct accuracy. #424

v0.7.3rc1 - 2025.03.14#

🎉 Hello, World! This is the first release candidate of v0.7.3 for vllm-ascend. Please follow the official doc to start the journey.

  • Quickstart with container: https://vllm-ascend.readthedocs.io/en/v0.7.3-dev/quick_start.html

  • Installation: https://vllm-ascend.readthedocs.io/en/v0.7.3-dev/installation.html

Highlights#

  • DeepSeek V3/R1 works well now. Read the official guide to start! #242

  • Speculative decoding feature is supported. #252

  • Multi step scheduler feature is supported. #300

Core#

  • Bump torch_npu version to dev20250308.3 to improve _exponential accuracy

  • Added initial support for pooling models. Bert based model, such as BAAI/bge-base-en-v1.5 and BAAI/bge-reranker-v2-m3 works now. #229

Model#

  • The performance of Qwen2-VL is improved. #241

  • MiniCPM is now supported #164

Other#

  • Support MTP(Multi-Token Prediction) for DeepSeek V3/R1 #236

  • [Docs] Added more model tutorials, include DeepSeek, QwQ, Qwen and Qwen 2.5VL. See the official doc for detail

  • Pin modelscope<1.23.0 on vLLM v0.7.3 to resolve: https://github.com/vllm-project/vllm/pull/13807

Known issues#

  • In some cases, especially when the input/output is very long, the accuracy of output may be incorrect. We are working on it. It’ll be fixed in the next release.

  • Improved and reduced the garbled code in model output. But if you still hit the issue, try to change the generation config value, such as temperature, and try again. There is also a knonwn issue shown below. Any feedback is welcome. #277

v0.7.1rc1 - 2025.02.19#

🎉 Hello, World!

We are excited to announce the first release candidate of v0.7.1 for vllm-ascend.

vLLM Ascend Plugin (vllm-ascend) is a community maintained hardware plugin for running vLLM on the Ascend NPU. With this release, users can now enjoy the latest features and improvements of vLLM on the Ascend NPU.

Please follow the official doc to start the journey. Note that this is a release candidate, and there may be some bugs or issues. We appreciate your feedback and suggestions here

Highlights#

  • Initial supports for Ascend NPU on vLLM. #3

  • DeepSeek is now supported. #88 #68

  • Qwen, Llama series and other popular models are also supported, you can see more details in here.

Core#

  • Added the Ascend quantization config option, the implementation will coming soon. #7 #73

  • Add silu_and_mul and rope ops and add mix ops into attention layer. #18

Other#

  • [CI] Enable Ascend CI to actively monitor and improve quality for vLLM on Ascend. #3

  • [Docker] Add vllm-ascend container image #64

  • [Docs] Add a live doc #55

Known issues#

  • This release relies on an unreleased torch_npu version. It has been installed within official container image already. Please install it manually if you are using non-container environment.

  • There are logs like No platform detected, vLLM is running on UnspecifiedPlatform or Failed to import from vllm._C with ModuleNotFoundError("No module named 'vllm._C'") shown when running vllm-ascend. It actually doesn’t affect any functionality and performance. You can just ignore it. And it has been fixed in this PR which will be included in v0.7.3 soon.

  • There are logs like # CPU blocks: 35064, # CPU blocks: 2730 shown when running vllm-ascend which should be # NPU blocks: . It actually doesn’t affect any functionality and performance. You can just ignore it. And it has been fixed in this PR which will be included in v0.7.3 soon.

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