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[ReleaseNote] Release note of v0.10.0rc1 (#2225)

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### What this PR does / why we need it?
Release note of v0.10.0rc1

- vLLM version: v0.10.0
- vLLM main:
8e8e0b6af1

---------

Signed-off-by: MengqingCao <cmq0113@163.com>
This commit is contained in:
Mengqing Cao
2025-08-07 14:46:49 +08:00
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# Release note
## v0.10.0rc1 - 2025.08.07
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.
### Highlights
* 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).
* W4A8 quantization method is supported for dense and MoE model now. [#2060](https://github.com/vllm-project/vllm-ascend/pull/2060) [#2172](https://github.com/vllm-project/vllm-ascend/pull/2172)
### Core
* 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.
* 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)
* 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)
* Pipeline Parallelism is supported in V1 now. [#1800](https://github.com/vllm-project/vllm-ascend/pull/1800)
* Prefix cache feature now work with the Ascend Scheduler. [#1446](https://github.com/vllm-project/vllm-ascend/pull/1446)
* Torchair graph mode works with tp > 4 now. [#1508](https://github.com/vllm-project/vllm-ascend/issues/1508)
* MTP support torchair graph mode now [#2145](https://github.com/vllm-project/vllm-ascend/pull/2145)
## Other
* Bug fixes:
* Fix functional problem of multi-modality models like Qwen2-audio with Aclgraph. [#1803](https://github.com/vllm-project/vllm-ascend/pull/1803)
* Fix the process group creating error with external launch scenario. [#1681](https://github.com/vllm-project/vllm-ascend/pull/1681)
* Fix the functional problem with guided decoding. [#2022](https://github.com/vllm-project/vllm-ascend/pull/2022)
* Fix the accuracy issue with common MoE models in DP scenario. [#1856](https://github.com/vllm-project/vllm-ascend/pull/1856)
* Performance improved through a lot of prs:
* Caching sin/cos instead of calculate it every layer. [#1890](https://github.com/vllm-project/vllm-ascend/pull/1890)
* Improve shared expert multi-stream parallelism [#1891](https://github.com/vllm-project/vllm-ascend/pull/1891)
* Implement the fusion of allreduce and matmul in prefill phase when tp is enabled. Enable this feature by setting `VLLM_ASCEND_ENABLE_MATMUL_ALLREDUCE` to `1`. [#1926](https://github.com/vllm-project/vllm-ascend/pull/1926)
* Optimize Quantized MoE Performance by Reducing All2All Communication. [#2195](https://github.com/vllm-project/vllm-ascend/pull/2195)
* Use AddRmsNormQuant ops in the custom model to optimize Qwen3's performance [#1806](https://github.com/vllm-project/vllm-ascend/pull/1806)
* Use multicast to avoid padding decode request to prefill size [#1555](https://github.com/vllm-project/vllm-ascend/pull/1555)
* The performance of LoRA has been improved. [#1884](https://github.com/vllm-project/vllm-ascend/pull/1884)
* A batch of refactoring prs to enhance the code architecture:
* Torchair model runner refactor [#2205](https://github.com/vllm-project/vllm-ascend/pull/2205)
* Refactoring forward_context and model_runner_v1. [#1979](https://github.com/vllm-project/vllm-ascend/pull/1979)
* Refactor AscendMetaData Comments. [#1967](https://github.com/vllm-project/vllm-ascend/pull/1967)
* Refactor torchair utils. [#1892](https://github.com/vllm-project/vllm-ascend/pull/1892)
* Refactor torchair worker. [#1885](https://github.com/vllm-project/vllm-ascend/pull/1885)
* Register activation customop instead of overwrite forward_oot. [#1841](https://github.com/vllm-project/vllm-ascend/pull/1841)
* Parameters changes:
* `expert_tensor_parallel_size` in `additional_config` is removed now, and the EP and TP is aligned with vLLM now. [#1681](https://github.com/vllm-project/vllm-ascend/pull/1681)
* Add `VLLM_ASCEND_MLA_PA` in environ variables, use this to enable mla paged attention operator for deepseek mla decode.
* Add `VLLM_ASCEND_ENABLE_MATMUL_ALLREDUCE` in environ variables, enable `MatmulAllReduce` fusion kernel when tensor parallel is enabled. This feature is supported in A2, and eager mode will get better performance.
* Add `VLLM_ASCEND_ENABLE_MOE_ALL2ALL_SEQ` in environ variables, Whether to enable moe all2all seq, this provides a basic framework on the basis of alltoall for easy expansion.
* UT coverage reached 76.34% after a batch of prs followed by this rfc: [#1298](https://github.com/vllm-project/vllm-ascend/issues/1298)
* Sequence Parallelism works for Qwen3 MoE. [#2209](https://github.com/vllm-project/vllm-ascend/issues/2209)
* Chinese online document is added now. [#1870](https://github.com/vllm-project/vllm-ascend/issues/1870)
### Known Issues
* Aclgraph could not work with DP + EP currently, the mainly gap is the number of npu stream that Aclgraph needed to capture graph is not enough. [#2229](https://github.com/vllm-project/vllm-ascend/issues/2229)
* There is an accuracy issue on W8A8 dynamic quantized DeepSeek with multistream enabled. This will be fixed in the next release. [#2232](https://github.com/vllm-project/vllm-ascend/issues/2232)
* In Qwen3 MoE, SP cannot be incorporated into the Aclgraph. [#2246](https://github.com/vllm-project/vllm-ascend/issues/2246)
* MTP not support V1 scheduler currently, will fix it in Q3. [#2254](https://github.com/vllm-project/vllm-ascend/issues/2254)
* 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)
## v0.9.1rc2 - 2025.08.04
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.