[Doc] Update doc url link (#5781)
Drop `dev` suffix for doc url.
Rename url to `https://docs.vllm.ai/projects/ascend`
- vLLM version: v0.13.0
- vLLM main:
2f4e6548ef
Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
This commit is contained in:
wangxiyuan
@@ -1,6 +1,6 @@
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# Release Notes
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## v0.13.0rc1 - 2025.12.27
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This is the first release candidate of v0.13.0 for vLLM Ascend. We landed lots of bug fix, performance improvement and feature support in this release. Any feedback is welcome to help us to improve vLLM Ascend. Please follow the [official doc](https://vllm-ascend.readthedocs.io/en/latest) to get started.
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This is the first release candidate of v0.13.0 for vLLM Ascend. We landed lots of bug fix, performance improvement and feature support in this release. Any feedback is welcome to help us to improve vLLM Ascend. Please follow the [official doc](https://docs.vllm.ai/projects/ascend/en/latest) to get started.
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### Highlights
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- Improved the performance of DeepSeek V3.2, please refer to [tutorials](https://docs.vllm.ai/projects/ascend/en/latest/tutorials/DeepSeek-V3.2.html)
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@@ -48,7 +48,7 @@ Some general performance improvement:
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- There is a precision issue with curl on ultra-short sequences in DeepSeek-V3.2. We'll fix it in next release. [#5370](https://github.com/vllm-project/vllm-ascend/issues/5370)
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## v0.11.0 - 2025.12.16
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We're excited to announce the release of v0.11.0 for vLLM Ascend. This is the official release for v0.11.0. Please follow the [official doc](https://vllm-ascend.readthedocs.io/en/v0.11.0-dev) to get started. We'll consider to release post version in the future if needed. This release note will only contain the important change and note from v0.11.0rc3.
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We're excited to announce the release of v0.11.0 for vLLM Ascend. This is the official release for v0.11.0. Please follow the [official doc](https://docs.vllm.ai/projects/ascend/en/v0.11.0) to get started. We'll consider to release post version in the future if needed. This release note will only contain the important change and note from v0.11.0rc3.
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### Highlights
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- Improved the performance for deepseek 3/3.1. [#3995](https://github.com/vllm-project/vllm-ascend/pull/3995)
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@@ -81,7 +81,7 @@ We're excited to announce the release of v0.11.0 for vLLM Ascend. This is the of
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## v0.12.0rc1 - 2025.12.13
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This is the first release candidate of v0.12.0 for vLLM Ascend. We landed lots of bug fix, performance improvement and feature support in this release. Any feedback is welcome to help us to improve vLLM Ascend. Please follow the [official doc](https://vllm-ascend.readthedocs.io/en/latest) to get started.
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This is the first release candidate of v0.12.0 for vLLM Ascend. We landed lots of bug fix, performance improvement and feature support in this release. Any feedback is welcome to help us to improve vLLM Ascend. Please follow the [official doc](https://docs.vllm.ai/projects/ascend/en/latest) to get started.
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### Highlights
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- DeepSeek 3.2 is stable and performance is improved. In this release, you don't need to install any other packages now. Following the [official tutorial](https://docs.vllm.ai/projects/ascend/en/latest/tutorials/DeepSeek-V3.2.html) to start using it.
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@@ -126,7 +126,7 @@ This is the first release candidate of v0.12.0 for vLLM Ascend. We landed lots o
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- speculative decode method `suffix` doesn't work. We'll fix it in next release. You can pick this commit to fix the issue: [#5010](https://github.com/vllm-project/vllm-ascend/pull/5010)
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## v0.11.0rc3 - 2025.12.03
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This is the third release candidate of v0.11.0 for vLLM Ascend. For quality reasons, we released a new rc before the official release. Thanks for all your feedback. Please follow the [official doc](https://vllm-ascend.readthedocs.io/en/v0.11.0-dev) to get started.
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This is the third release candidate of v0.11.0 for vLLM Ascend. For quality reasons, we released a new rc before the official release. Thanks for all your feedback. Please follow the [official doc](https://docs.vllm.ai/projects/ascend/en/v0.11.0) to get started.
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### Highlights
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- torch-npu is upgraded to 2.7.1.post1. Please note that the package is pushed to [pypi mirror](https://mirrors.huaweicloud.com/ascend/repos/pypi/torch-npu/). So it's hard to add it to auto dependence. Please install it by yourself.
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@@ -142,7 +142,7 @@ This is the third release candidate of v0.11.0 for vLLM Ascend. For quality reas
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- Fix a function bug when running qwen2.5 vl under high concurrency. [#4553](https://github.com/vllm-project/vllm-ascend/pull/4553)
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## v0.11.0rc2 - 2025.11.21
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This is the second release candidate of v0.11.0 for vLLM Ascend. In this release, we solved many bugs to improve the quality. Thanks for all your feedback. We'll keep working on bug fix and performance improvement. The v0.11.0 official release will come soon. Please follow the [official doc](https://vllm-ascend.readthedocs.io/en/v0.11.0-dev) to get started.
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This is the second release candidate of v0.11.0 for vLLM Ascend. In this release, we solved many bugs to improve the quality. Thanks for all your feedback. We'll keep working on bug fix and performance improvement. The v0.11.0 official release will come soon. Please follow the [official doc](https://docs.vllm.ai/projects/ascend/en/v0.11.0) to get started.
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### Highlights
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- CANN is upgraded to 8.3.RC2. [#4332](https://github.com/vllm-project/vllm-ascend/pull/4332)
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@@ -171,7 +171,7 @@ This is the second release candidate of v0.11.0 for vLLM Ascend. In this release
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## v0.11.0rc1 - 2025.11.10
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This is the first release candidate of v0.11.0 for vLLM Ascend. Please follow the [official doc](https://vllm-ascend.readthedocs.io/en/v0.11.0-dev) to get started.
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This is the first release candidate of v0.11.0 for vLLM Ascend. Please follow the [official doc](https://docs.vllm.ai/projects/ascend/en/v0.11.0) to get started.
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v0.11.0 will be the next official release version of vLLM Ascend. We'll release it in the next few days. Any feedback is welcome to help us to improve v0.11.0.
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### Highlights
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@@ -203,7 +203,7 @@ v0.11.0 will be the next official release version of vLLM Ascend. We'll release
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## v0.11.0rc0 - 2025.09.30
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This is the special release candidate of v0.11.0 for vLLM Ascend. Please follow the [official doc](https://vllm-ascend.readthedocs.io/en/) to get started.
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This is the special release candidate of v0.11.0 for vLLM Ascend. Please follow the [official doc](https://docs.vllm.ai/projects/ascend/en/) to get started.
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### Highlights
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@@ -227,11 +227,11 @@ This is the special release candidate of v0.11.0 for vLLM Ascend. Please follow
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## v0.10.2rc1 - 2025.09.16
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This is the 1st release candidate of v0.10.2 for vLLM Ascend. Please follow the [official doc](https://vllm-ascend.readthedocs.io/en/) to get started.
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This is the 1st release candidate of v0.10.2 for vLLM Ascend. Please follow the [official doc](https://docs.vllm.ai/projects/ascend/en/) to get started.
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### Highlights
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- Added support for Qwen3-Next. Please note that the expert parallel and MTP features do not work with this release. We will be adding support for them soon. Follow the [official guide](https://vllm-ascend.readthedocs.io/en/latest/tutorials/multi_npu_qwen3_next.html) to get started. [#2917](https://github.com/vllm-project/vllm-ascend/pull/2917)
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- Added support for Qwen3-Next. Please note that the expert parallel and MTP features do not work with this release. We will be adding support for them soon. Follow the [official guide](https://docs.vllm.ai/projects/ascend/en/latest/tutorials/multi_npu_qwen3_next.html) to get started. [#2917](https://github.com/vllm-project/vllm-ascend/pull/2917)
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- Added quantization support for aclgraph [#2841](https://github.com/vllm-project/vllm-ascend/pull/2841)
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### Core
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@@ -268,7 +268,7 @@ This is the 1st release candidate of v0.10.2 for vLLM Ascend. Please follow the
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## v0.10.1rc1 - 2025.09.04
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This is the 1st release candidate of v0.10.1 for vLLM Ascend. Please follow the [official doc](https://vllm-ascend.readthedocs.io/en/) to get started.
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This is the 1st release candidate of v0.10.1 for vLLM Ascend. Please follow the [official doc](https://docs.vllm.ai/projects/ascend/en/) to get started.
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### Highlights
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- LoRA Performance improved much through adding Custom Kernels by China Merchants Bank. [#2325](https://github.com/vllm-project/vllm-ascend/pull/2325)
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@@ -320,19 +320,19 @@ This is the 1st release candidate of v0.10.1 for vLLM Ascend. Please follow the
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We are excited to announce the newest official release of vLLM Ascend. This release includes many feature supports, performance improvements and bug fixes. We recommend users to upgrade from 0.7.3 to this version. Please always set `VLLM_USE_V1=1` to use V1 engine.
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In this release, we added many enhancements for large scale expert parallel case. It's recommended to follow the [official guide](https://vllm-ascend.readthedocs.io/en/v0.9.1-dev/tutorials/large_scale_ep.html).
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In this release, we added many enhancements for large scale expert parallel case. It's recommended to follow the [official guide](https://docs.vllm.ai/projects/ascend/en/v0.9.1/tutorials/large_scale_ep.html).
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Please note that this release note will list all the important changes from last official release(v0.7.3)
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### Highlights
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- DeepSeek V3/R1 is supported with high quality and performance. MTP can work with DeepSeek as well. Please refer to [muliti node tutorials](https://vllm-ascend.readthedocs.io/en/v0.9.1-dev/tutorials/multi_node.html) and [Large Scale Expert Parallelism](https://vllm-ascend.readthedocs.io/en/v0.9.1-dev/tutorials/large_scale_ep.html).
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- Qwen series models work with graph mode now. It works by default with V1 Engine. Please refer to [Qwen tutorials](https://vllm-ascend.readthedocs.io/en/v0.9.1-dev/tutorials/index.html).
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- Disaggregated Prefilling support for V1 Engine. Please refer to [Large Scale Expert Parallelism](https://vllm-ascend.readthedocs.io/en/v0.9.1-dev/tutorials/large_scale_ep.html) tutorials.
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- DeepSeek V3/R1 is supported with high quality and performance. MTP can work with DeepSeek as well. Please refer to [muliti node tutorials](https://docs.vllm.ai/projects/ascend/en/v0.9.1/tutorials/multi_node.html) and [Large Scale Expert Parallelism](https://docs.vllm.ai/projects/ascend/en/v0.9.1/tutorials/large_scale_ep.html).
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- Qwen series models work with graph mode now. It works by default with V1 Engine. Please refer to [Qwen tutorials](https://docs.vllm.ai/projects/ascend/en/v0.9.1/tutorials/index.html).
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- Disaggregated Prefilling support for V1 Engine. Please refer to [Large Scale Expert Parallelism](https://docs.vllm.ai/projects/ascend/en/v0.9.1/tutorials/large_scale_ep.html) tutorials.
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- Automatic prefix caching and chunked prefill feature is supported.
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- Speculative decoding feature works with Ngram and MTP method.
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- MOE and dense w4a8 quantization support now. Please refer to [quantization guide](https://vllm-ascend.readthedocs.io/en/v0.9.1-dev/user_guide/feature_guide/quantization.html).
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- Sleep Mode feature is supported for V1 engine. Please refer to [Sleep mode tutorials](https://vllm-ascend.readthedocs.io/en/v0.9.1-dev/user_guide/feature_guide/sleep_mode.html).
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- MOE and dense w4a8 quantization support now. Please refer to [quantization guide](https://docs.vllm.ai/projects/ascend/en/v0.9.1/user_guide/feature_guide/quantization.html).
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- Sleep Mode feature is supported for V1 engine. Please refer to [Sleep mode tutorials](https://docs.vllm.ai/projects/ascend/en/v0.9.1/user_guide/feature_guide/sleep_mode.html).
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- Dynamic and Static EPLB support is added. This feature is still experimental.
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### Note
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@@ -364,7 +364,7 @@ The following notes are especially for reference when upgrading from last final
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## v0.9.1rc3 - 2025.08.22
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This is the 3rd release candidate of v0.9.1 for vLLM Ascend. Please follow the [official doc](https://vllm-ascend.readthedocs.io/en/v0.9.1-dev/) to get started.
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This is the 3rd release candidate of v0.9.1 for vLLM Ascend. Please follow the [official doc](https://docs.vllm.ai/projects/ascend/en/v0.9.1/) to get started.
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### Core
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@@ -394,7 +394,7 @@ This is the 3rd release candidate of v0.9.1 for vLLM Ascend. Please follow the [
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## v0.10.0rc1 - 2025.08.07
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This is the 1st release candidate of v0.10.0 for vLLM Ascend. Please follow the [official doc](https://vllm-ascend.readthedocs.io/en/) to get started. V0 is completely removed from this version.
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This is the 1st release candidate of v0.10.0 for vLLM Ascend. Please follow the [official doc](https://docs.vllm.ai/projects/ascend/en/) to get started. V0 is completely removed from this version.
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### Highlights
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- Disaggregate prefill works with V1 engine now. You can take a try with DeepSeek model [#950](https://github.com/vllm-project/vllm-ascend/pull/950), following this [tutorial](https://github.com/vllm-project/vllm-ascend/blob/main/examples/disaggregated_prefill_v1/README.md).
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@@ -403,7 +403,7 @@ This is the 1st release candidate of v0.10.0 for vLLM Ascend. Please follow the
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### Core
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- Ascend PyTorch adapter (torch_npu) has been upgraded to `2.7.1.dev20250724`. [#1562](https://github.com/vllm-project/vllm-ascend/pull/1562) And CANN hase been upgraded to `8.2.RC1`. [#1653](https://github.com/vllm-project/vllm-ascend/pull/1653) Don’t forget to update them in your environment or using the latest images.
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- vLLM Ascend works on Atlas 800I A3 now, and the image on A3 will be released from this version on. [#1582](https://github.com/vllm-project/vllm-ascend/pull/1582)
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- Kimi-K2 with w8a8 quantization, Qwen3-Coder and GLM-4.5 is supported in vLLM Ascend, please following this [tutorial](https://vllm-ascend.readthedocs.io/en/latest/tutorials/multi_node_kimi.md.html) to have a try. [#2162](https://github.com/vllm-project/vllm-ascend/pull/2162)
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- Kimi-K2 with w8a8 quantization, Qwen3-Coder and GLM-4.5 is supported in vLLM Ascend, please following this [tutorial](https://docs.vllm.ai/projects/ascend/en/latest/tutorials/multi_node_kimi.md.html) to have a try. [#2162](https://github.com/vllm-project/vllm-ascend/pull/2162)
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- Pipeline Parallelism is supported in V1 now. [#1800](https://github.com/vllm-project/vllm-ascend/pull/1800)
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- Prefix cache feature now work with the Ascend Scheduler. [#1446](https://github.com/vllm-project/vllm-ascend/pull/1446)
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- Torchair graph mode works with tp > 4 now. [#1508](https://github.com/vllm-project/vllm-ascend/issues/1508)
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@@ -449,7 +449,7 @@ This is the 1st release candidate of v0.10.0 for vLLM Ascend. Please follow the
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- When running MTP with DP > 1, we need to disable metrics logger due to some issue on vLLM. [#2254](https://github.com/vllm-project/vllm-ascend/issues/2254)
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## v0.9.1rc2 - 2025.08.04
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This is the 2nd release candidate of v0.9.1 for vLLM Ascend. Please follow the [official doc](https://vllm-ascend.readthedocs.io/en/v0.9.1-dev/) to get started.
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This is the 2nd release candidate of v0.9.1 for vLLM Ascend. Please follow the [official doc](https://docs.vllm.ai/projects/ascend/en/v0.9.1/) to get started.
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### Highlights
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- MOE and dense w4a8 quantization support now: [#1320](https://github.com/vllm-project/vllm-ascend/pull/1320) [#1910](https://github.com/vllm-project/vllm-ascend/pull/1910) [#1275](https://github.com/vllm-project/vllm-ascend/pull/1275) [#1480](https://github.com/vllm-project/vllm-ascend/pull/1480)
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@@ -554,7 +554,7 @@ This is the 2nd release candidate of v0.9.1 for vLLM Ascend. Please follow the [
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## v0.9.2rc1 - 2025.07.11
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This is the 1st release candidate of v0.9.2 for vLLM Ascend. Please follow the [official doc](https://vllm-ascend.readthedocs.io/en/) 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.
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This is the 1st release candidate of v0.9.2 for vLLM Ascend. Please follow the [official doc](https://docs.vllm.ai/projects/ascend/en/) 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.
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### Highlights
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- Pooling model works with V1 engine now. You can take a try with Qwen3 embedding model [#1359](https://github.com/vllm-project/vllm-ascend/pull/1359).
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@@ -601,7 +601,7 @@ This is the 1st release candidate of v0.9.2 for vLLM Ascend. Please follow the [
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## v0.9.1rc1 - 2025.06.22
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This is the 1st release candidate of v0.9.1 for vLLM Ascend. Please follow the [official doc](https://vllm-ascend.readthedocs.io/en/) to get started.
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This is the 1st release candidate of v0.9.1 for vLLM Ascend. Please follow the [official doc](https://docs.vllm.ai/projects/ascend/en/) to get started.
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### Experimental
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@@ -657,11 +657,11 @@ This release contains some quick fixes for v0.9.0rc1. Please use this release in
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## v0.9.0rc1 - 2025.06.09
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This is the 1st release candidate of v0.9.0 for vllm-ascend. Please follow the [official doc](https://vllm-ascend.readthedocs.io/en/) 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.
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This is the 1st release candidate of v0.9.0 for vllm-ascend. Please follow the [official doc](https://docs.vllm.ai/projects/ascend/en/) 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.
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### Highlights
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- DeepSeek works with graph mode now. Follow the [official doc](https://vllm-ascend.readthedocs.io/en/latest/user_guide/feature_guide/graph_mode.html) to take a try. [#789](https://github.com/vllm-project/vllm-ascend/pull/789)
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- DeepSeek works with graph mode now. Follow the [official doc](https://docs.vllm.ai/projects/ascend/en/latest/user_guide/feature_guide/graph_mode.html) to take a try. [#789](https://github.com/vllm-project/vllm-ascend/pull/789)
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- Qwen series models work 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.
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### Core
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@@ -686,7 +686,7 @@ This is the 1st release candidate of v0.9.0 for vllm-ascend. Please follow the [
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- A batch of bugs for graph mode and moe model have been fixed. [#773](https://github.com/vllm-project/vllm-ascend/pull/773) [#771](https://github.com/vllm-project/vllm-ascend/pull/771) [#774](https://github.com/vllm-project/vllm-ascend/pull/774) [#816](https://github.com/vllm-project/vllm-ascend/pull/816) [#817](https://github.com/vllm-project/vllm-ascend/pull/817) [#819](https://github.com/vllm-project/vllm-ascend/pull/819) [#912](https://github.com/vllm-project/vllm-ascend/pull/912) [#897](https://github.com/vllm-project/vllm-ascend/pull/897) [#961](https://github.com/vllm-project/vllm-ascend/pull/961) [#958](https://github.com/vllm-project/vllm-ascend/pull/958) [#913](https://github.com/vllm-project/vllm-ascend/pull/913) [#905](https://github.com/vllm-project/vllm-ascend/pull/905)
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- A batch of performance improvement PRs have been merged. [#784](https://github.com/vllm-project/vllm-ascend/pull/784) [#803](https://github.com/vllm-project/vllm-ascend/pull/803) [#966](https://github.com/vllm-project/vllm-ascend/pull/966) [#839](https://github.com/vllm-project/vllm-ascend/pull/839) [#970](https://github.com/vllm-project/vllm-ascend/pull/970) [#947](https://github.com/vllm-project/vllm-ascend/pull/947) [#987](https://github.com/vllm-project/vllm-ascend/pull/987) [#1085](https://github.com/vllm-project/vllm-ascend/pull/1085)
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- From this release, binary wheel package will be released as well. [#775](https://github.com/vllm-project/vllm-ascend/pull/775)
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||||
- The contributor doc site is [added](https://vllm-ascend.readthedocs.io/en/latest/community/contributors.html)
|
||||
- The contributor doc site is [added](https://docs.vllm.ai/projects/ascend/en/latest/community/contributors.html)
|
||||
|
||||
### Known Issue
|
||||
|
||||
@@ -695,12 +695,12 @@ This is the 1st release candidate of v0.9.0 for vllm-ascend. Please follow the [
|
||||
|
||||
## v0.7.3.post1 - 2025.05.29
|
||||
|
||||
This is the first post release of 0.7.3. Please follow the [official doc](https://vllm-ascend.readthedocs.io/en/v0.7.3-dev) to start the journey. It includes the following changes:
|
||||
This is the first post release of 0.7.3. Please follow the [official doc](https://docs.vllm.ai/projects/ascend/en/v0.7.3) 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 recommended to improve the performance of Qwen3. [#903](https://github.com/vllm-project/vllm-ascend/pull/903) [#915](https://github.com/vllm-project/vllm-ascend/pull/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](https://github.com/vllm-project/vllm-ascend/pull/878) [Doc Link](https://vllm-ascend.readthedocs.io/en/v0.7.3-dev/developer_guide/performance/optimization_and_tuning.html)
|
||||
- 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](https://github.com/vllm-project/vllm-ascend/pull/878) [Doc Link](https://docs.vllm.ai/projects/ascend/en/v0.7.3/developer_guide/performance/optimization_and_tuning.html)
|
||||
|
||||
### Bug Fixes
|
||||
|
||||
@@ -719,10 +719,10 @@ This is the first post release of 0.7.3. Please follow the [official doc](https:
|
||||
|
||||
🎉 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](https://vllm-ascend.readthedocs.io/en/v0.7.3-dev) to start the journey.
|
||||
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](https://docs.vllm.ai/projects/ascend/en/v0.7.3) to start the journey.
|
||||
|
||||
### Highlights
|
||||
- This release includes all features landed in the previous release candidates ([v0.7.1rc1](https://github.com/vllm-project/vllm-ascend/releases/tag/v0.7.1rc1), [v0.7.3rc1](https://github.com/vllm-project/vllm-ascend/releases/tag/v0.7.3rc1), [v0.7.3rc2](https://github.com/vllm-project/vllm-ascend/releases/tag/v0.7.3rc2)). And all the features are fully tested and verified. Visit the official doc the get the detail [feature](https://vllm-ascend.readthedocs.io/en/v0.7.3-dev/user_guide/suppoted_features.html) and [model](https://vllm-ascend.readthedocs.io/en/v0.7.3-dev/user_guide/supported_models.html) support matrix.
|
||||
- This release includes all features landed in the previous release candidates ([v0.7.1rc1](https://github.com/vllm-project/vllm-ascend/releases/tag/v0.7.1rc1), [v0.7.3rc1](https://github.com/vllm-project/vllm-ascend/releases/tag/v0.7.3rc1), [v0.7.3rc2](https://github.com/vllm-project/vllm-ascend/releases/tag/v0.7.3rc2)). And all the features are fully tested and verified. Visit the official doc the get the detail [feature](https://docs.vllm.ai/projects/ascend/en/v0.7.3/user_guide/suppoted_features.html) and [model](https://docs.vllm.ai/projects/ascend/en/v0.7.3/user_guide/supported_models.html) 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](https://github.com/vllm-project/vllm-ascend/pull/662)
|
||||
- Integrate MindIE Turbo into vLLM Ascend to improve DeepSeek V3/R1, Qwen 2 series performance. [#708](https://github.com/vllm-project/vllm-ascend/pull/708)
|
||||
@@ -742,7 +742,7 @@ We are excited to announce the release of 0.7.3 for vllm-ascend. This is the fir
|
||||
|
||||
## v0.8.5rc1 - 2025.05.06
|
||||
|
||||
This is the 1st release candidate of v0.8.5 for vllm-ascend. Please follow the [official doc](https://vllm-ascend.readthedocs.io/en/) 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](https://vllm-ascend.readthedocs.io/en/latest/user_guide/support_matrix/supported_features.html).
|
||||
This is the 1st release candidate of v0.8.5 for vllm-ascend. Please follow the [official doc](https://docs.vllm.ai/projects/ascend/en/) 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](https://docs.vllm.ai/projects/ascend/en/latest/user_guide/support_matrix/supported_features.html).
|
||||
|
||||
### Highlights
|
||||
- Upgrade CANN version to 8.1.RC1 to support chunked prefill and automatic prefix caching (`--enable_prefix_caching`) when V1 is enabled [#747](https://github.com/vllm-project/vllm-ascend/pull/747)
|
||||
@@ -765,11 +765,11 @@ This is the 1st release candidate of v0.8.5 for vllm-ascend. Please follow the [
|
||||
|
||||
## v0.8.4rc2 - 2025.04.29
|
||||
|
||||
This is the second release candidate of v0.8.4 for vllm-ascend. Please follow the [official doc](https://vllm-ascend.readthedocs.io/en/) 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.
|
||||
This is the second release candidate of v0.8.4 for vllm-ascend. Please follow the [official doc](https://docs.vllm.ai/projects/ascend/en/) 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](https://vllm-ascend.readthedocs.io/en/latest/tutorials/single_npu.html) to run the quick demo. [#709](https://github.com/vllm-project/vllm-ascend/pull/709)
|
||||
- Ascend W8A8 quantization method is supported now. Please take the [official doc](https://vllm-ascend.readthedocs.io/en/latest/tutorials/multi_npu_quantization.html) for example. Any [feedback](https://github.com/vllm-project/vllm-ascend/issues/619) is welcome. [#580](https://github.com/vllm-project/vllm-ascend/pull/580)
|
||||
- Qwen3 and Qwen3MOE is supported now. Please follow the [official doc](https://docs.vllm.ai/projects/ascend/en/latest/tutorials/single_npu.html) to run the quick demo. [#709](https://github.com/vllm-project/vllm-ascend/pull/709)
|
||||
- Ascend W8A8 quantization method is supported now. Please take the [official doc](https://docs.vllm.ai/projects/ascend/en/latest/tutorials/multi_npu_quantization.html) for example. Any [feedback](https://github.com/vllm-project/vllm-ascend/issues/619) is welcome. [#580](https://github.com/vllm-project/vllm-ascend/pull/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](https://github.com/vllm-project/vllm-ascend/pull/429) [#585](https://github.com/vllm-project/vllm-ascend/pull/585) [#626](https://github.com/vllm-project/vllm-ascend/pull/626) [#636](https://github.com/vllm-project/vllm-ascend/pull/636) [#671](https://github.com/vllm-project/vllm-ascend/pull/671)
|
||||
|
||||
### Core
|
||||
@@ -785,7 +785,7 @@ This is the second release candidate of v0.8.4 for vllm-ascend. Please follow th
|
||||
|
||||
## v0.8.4rc1 - 2025.04.18
|
||||
|
||||
This is the first release candidate of v0.8.4 for vllm-ascend. Please follow the [official doc](https://vllm-ascend.readthedocs.io/en/) 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](https://vllm-ascend.readthedocs.io/en/latest/community/versioning_policy.html#release-window).
|
||||
This is the first release candidate of v0.8.4 for vllm-ascend. Please follow the [official doc](https://docs.vllm.ai/projects/ascend/en/) 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](https://docs.vllm.ai/projects/ascend/en/latest/community/versioning_policy.html#release-window).
|
||||
|
||||
### Highlights
|
||||
|
||||
@@ -808,9 +808,9 @@ This is the first release candidate of v0.8.4 for vllm-ascend. Please follow the
|
||||
|
||||
## v0.7.3rc2 - 2025.03.29
|
||||
|
||||
This is 2nd release candidate of v0.7.3 for vllm-ascend. Please follow the [official doc](https://vllm-ascend.readthedocs.io/en/v0.7.3-dev) 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
|
||||
This is 2nd release candidate of v0.7.3 for vllm-ascend. Please follow the [official doc](https://docs.vllm.ai/projects/ascend/en/v0.7.3) to start the journey.
|
||||
- Quickstart with container: https://docs.vllm.ai/projects/ascend/en/v0.7.3/quick_start.html
|
||||
- Installation: https://docs.vllm.ai/projects/ascend/en/v0.7.3/installation.html
|
||||
|
||||
### Highlights
|
||||
- Add Ascend Custom Ops framework. 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](https://github.com/vllm-project/vllm-ascend/pull/371)
|
||||
@@ -830,12 +830,12 @@ This is 2nd release candidate of v0.7.3 for vllm-ascend. Please follow the [offi
|
||||
|
||||
## 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](https://vllm-ascend.readthedocs.io/en/v0.7.3-dev) 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
|
||||
🎉 Hello, World! This is the first release candidate of v0.7.3 for vllm-ascend. Please follow the [official doc](https://docs.vllm.ai/projects/ascend/en/v0.7.3) to start the journey.
|
||||
- Quickstart with container: https://docs.vllm.ai/projects/ascend/en/v0.7.3/quick_start.html
|
||||
- Installation: https://docs.vllm.ai/projects/ascend/en/v0.7.3/installation.html
|
||||
|
||||
### Highlights
|
||||
- DeepSeek V3/R1 works well now. Read the [official guide](https://vllm-ascend.readthedocs.io/en/v0.7.3-dev/tutorials/multi_node.html) to start! [#242](https://github.com/vllm-project/vllm-ascend/pull/242)
|
||||
- DeepSeek V3/R1 works well now. Read the [official guide](https://docs.vllm.ai/projects/ascend/en/v0.7.3/tutorials/multi_node.html) to start! [#242](https://github.com/vllm-project/vllm-ascend/pull/242)
|
||||
- Speculative decoding feature is supported. [#252](https://github.com/vllm-project/vllm-ascend/pull/252)
|
||||
- Multi step scheduler feature is supported. [#300](https://github.com/vllm-project/vllm-ascend/pull/300)
|
||||
|
||||
@@ -849,7 +849,7 @@ This is 2nd release candidate of v0.7.3 for vllm-ascend. Please follow the [offi
|
||||
|
||||
### Others
|
||||
- Support MTP(Multi-Token Prediction) for DeepSeek V3/R1 [#236](https://github.com/vllm-project/vllm-ascend/pull/236)
|
||||
- [Docs] Added more model tutorials, include DeepSeek, QwQ, Qwen and Qwen 2.5VL. See the [official doc](https://vllm-ascend.readthedocs.io/en/v0.7.3-dev/tutorials/index.html) for detail
|
||||
- [Docs] Added more model tutorials, include DeepSeek, QwQ, Qwen and Qwen 2.5VL. See the [official doc](https://docs.vllm.ai/projects/ascend/en/v0.7.3/tutorials/index.html) for detail
|
||||
- Pin modelscope<1.23.0 on vLLM v0.7.3 to resolve: https://github.com/vllm-project/vllm/pull/13807
|
||||
|
||||
### Known Issues
|
||||
@@ -864,13 +864,13 @@ 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](https://vllm-ascend.readthedocs.io/en/v0.7.1-dev) 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](https://github.com/vllm-project/vllm-ascend/issues/19)
|
||||
Please follow the [official doc](https://docs.vllm.ai/projects/ascend/en/v0.7.1) 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](https://github.com/vllm-project/vllm-ascend/issues/19)
|
||||
|
||||
### Highlights
|
||||
|
||||
- Initial supports for Ascend NPU on vLLM. [#3](https://github.com/vllm-project/vllm-ascend/pull/3)
|
||||
- DeepSeek is now supported. [#88](https://github.com/vllm-project/vllm-ascend/pull/88) [#68](https://github.com/vllm-project/vllm-ascend/pull/68)
|
||||
- Qwen, Llama series and other popular models are also supported, you can see more details in [here](https://vllm-ascend.readthedocs.io/en/latest/user_guide/supported_models.html).
|
||||
- Qwen, Llama series and other popular models are also supported, you can see more details in [here](https://docs.vllm.ai/projects/ascend/en/latest/user_guide/supported_models.html).
|
||||
|
||||
### Core
|
||||
|
||||
@@ -885,6 +885,6 @@ Please follow the [official doc](https://vllm-ascend.readthedocs.io/en/v0.7.1-de
|
||||
|
||||
### Known Issues
|
||||
|
||||
- This release relies on an unreleased torch_npu version. It has been installed within official container image already. Please [install](https://vllm-ascend.readthedocs.io/en/v0.7.1rc1/installation.html) it manually if you are using non-container environment.
|
||||
- This release relies on an unreleased torch_npu version. It has been installed within official container image already. Please [install](https://docs.vllm.ai/projects/ascend/en/v0.7.1rc1/installation.html) 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](https://github.com/vllm-project/vllm/pull/12432) 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](https://github.com/vllm-project/vllm/pull/13378) which will be included in v0.7.3 soon.
|
||||
|
||||
Reference in New Issue
Block a user