[main]update release note & support matrix (#6759)

### What this PR does / why we need it?

Update release note & support matrix to add experimental tag for
features and models.

### Does this PR introduce _any_ user-facing change?

### How was this patch tested?

- vLLM version: v0.15.0
- vLLM main:
9562912cea

0.13.0 branch: https://github.com/vllm-project/vllm-ascend/pull/6751

Signed-off-by: zzzzwwjj <1183291235@qq.com>
This commit is contained in:
zzzzwwjj
2026-02-24 17:39:35 +08:00
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parent a8e951e6f5
commit 5c8ab7af39
3 changed files with 74 additions and 77 deletions

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@@ -8,32 +8,32 @@ This is the final release of v0.13.0 for vLLM Ascend. Please follow the [officia
**Model Support**
- **DeepSeek-R1 & DeepSeek-V3.2**: Performance optimizations, and async scheduling enhancements. [#3631](https://github.com/vllm-project/vllm-ascend/pull/3631) [#3900](https://github.com/vllm-project/vllm-ascend/pull/3900) [#3908](https://github.com/vllm-project/vllm-ascend/pull/3908) [#4191](https://github.com/vllm-project/vllm-ascend/pull/4191) [#4805](https://github.com/vllm-project/vllm-ascend/pull/4805)
- **Qwen3-Next**: Full support for Qwen3-Next series including 80B-A3B-Instruct with full graph mode, MTP, quantization (W8A8), NZ optimization, and chunked prefill. Fixed multiple accuracy and stability issues. [#3450](https://github.com/vllm-project/vllm-ascend/pull/3450) [#3572](https://github.com/vllm-project/vllm-ascend/pull/3572) [#3428](https://github.com/vllm-project/vllm-ascend/pull/3428) [#3918](https://github.com/vllm-project/vllm-ascend/pull/3918) [#4058](https://github.com/vllm-project/vllm-ascend/pull/4058) [#4245](https://github.com/vllm-project/vllm-ascend/pull/4245) [#4070](https://github.com/vllm-project/vllm-ascend/pull/4070) [#4477](https://github.com/vllm-project/vllm-ascend/pull/4477) [#4770](https://github.com/vllm-project/vllm-ascend/pull/4770)
- **DeepSeek-R1 & DeepSeek-V3.2**: [Experimental]Performance optimizations, and async scheduling enhancements. [#3631](https://github.com/vllm-project/vllm-ascend/pull/3631) [#3900](https://github.com/vllm-project/vllm-ascend/pull/3900) [#3908](https://github.com/vllm-project/vllm-ascend/pull/3908) [#4191](https://github.com/vllm-project/vllm-ascend/pull/4191) [#4805](https://github.com/vllm-project/vllm-ascend/pull/4805)
- **Qwen3-Next**: [Experimental]Full support for Qwen3-Next series including 80B-A3B-Instruct with full graph mode, MTP, quantization (W8A8), NZ optimization, and chunked prefill. Fixed multiple accuracy and stability issues. [#3450](https://github.com/vllm-project/vllm-ascend/pull/3450) [#3572](https://github.com/vllm-project/vllm-ascend/pull/3572) [#3428](https://github.com/vllm-project/vllm-ascend/pull/3428) [#3918](https://github.com/vllm-project/vllm-ascend/pull/3918) [#4058](https://github.com/vllm-project/vllm-ascend/pull/4058) [#4245](https://github.com/vllm-project/vllm-ascend/pull/4245) [#4070](https://github.com/vllm-project/vllm-ascend/pull/4070) [#4477](https://github.com/vllm-project/vllm-ascend/pull/4477) [#4770](https://github.com/vllm-project/vllm-ascend/pull/4770)
- **InternVL**: Added support for InternVL models with comprehensive e2e tests and accuracy evaluation. [#3796](https://github.com/vllm-project/vllm-ascend/pull/3796) [#3964](https://github.com/vllm-project/vllm-ascend/pull/3964)
- **LongCat-Flash**: Added support for LongCat-Flash model. [#3833](https://github.com/vllm-project/vllm-ascend/pull/3833)
- **minimax_m2**: Added support for minimax_m2 model. [#5624](https://github.com/vllm-project/vllm-ascend/pull/5624)
- **Whisper & Cross-Attention**: Added support for cross-attention and Whisper models. [#5592](https://github.com/vllm-project/vllm-ascend/pull/5592)
- **Pooling Models**: Added support for pooling models with PCP adaptation and fixed multiple pooling-related bugs. [#3122](https://github.com/vllm-project/vllm-ascend/pull/3122) [#4143](https://github.com/vllm-project/vllm-ascend/pull/4143) [#6056](https://github.com/vllm-project/vllm-ascend/pull/6056) [#6057](https://github.com/vllm-project/vllm-ascend/pull/6057) [#6146](https://github.com/vllm-project/vllm-ascend/pull/6146)
- **PanguUltraMoE**: Added support for PanguUltraMoE model. [#4615](https://github.com/vllm-project/vllm-ascend/pull/4615)
- **LongCat-Flash**: [Experimental]Added support for LongCat-Flash model. [#3833](https://github.com/vllm-project/vllm-ascend/pull/3833)
- **minimax_m2**: [Experimental]Added support for minimax_m2 model. [#5624](https://github.com/vllm-project/vllm-ascend/pull/5624)
- **Whisper & Cross-Attention**: [Experimental]Added support for cross-attention and Whisper models. [#5592](https://github.com/vllm-project/vllm-ascend/pull/5592)
- **Pooling Models**: [Experimental]Added support for pooling models with PCP adaptation and fixed multiple pooling-related bugs. [#3122](https://github.com/vllm-project/vllm-ascend/pull/3122) [#4143](https://github.com/vllm-project/vllm-ascend/pull/4143) [#6056](https://github.com/vllm-project/vllm-ascend/pull/6056) [#6057](https://github.com/vllm-project/vllm-ascend/pull/6057) [#6146](https://github.com/vllm-project/vllm-ascend/pull/6146)
- **PanguUltraMoE**: [Experimental]Added support for PanguUltraMoE model. [#4615](https://github.com/vllm-project/vllm-ascend/pull/4615)
**Core Features**
- **Context Parallel (PCP/DCP)**: [Experimental] Added comprehensive support for Prefill Context Parallel (PCP) and Decode Context Parallel (DCP) with ACLGraph, MTP, chunked prefill, MLAPO, and Mooncake connector integration. This is an experimental feature - feedback welcome. [#3260](https://github.com/vllm-project/vllm-ascend/pull/3260) [#3731](https://github.com/vllm-project/vllm-ascend/pull/3731) [#3801](https://github.com/vllm-project/vllm-ascend/pull/3801) [#3980](https://github.com/vllm-project/vllm-ascend/pull/3980) [#4066](https://github.com/vllm-project/vllm-ascend/pull/4066) [#4098](https://github.com/vllm-project/vllm-ascend/pull/4098) [#4183](https://github.com/vllm-project/vllm-ascend/pull/4183) [#5672](https://github.com/vllm-project/vllm-ascend/pull/5672)
- **Full Graph Mode (ACLGraph)**: Enhanced full graph mode with GQA support, memory optimizations, unified logic between ACLGraph and Torchair, and improved stability. [#3560](https://github.com/vllm-project/vllm-ascend/pull/3560) [#3970](https://github.com/vllm-project/vllm-ascend/pull/3970) [#3812](https://github.com/vllm-project/vllm-ascend/pull/3812) [#3879](https://github.com/vllm-project/vllm-ascend/pull/3879) [#3888](https://github.com/vllm-project/vllm-ascend/pull/3888) [#3894](https://github.com/vllm-project/vllm-ascend/pull/3894) [#5118](https://github.com/vllm-project/vllm-ascend/pull/5118)
- **Full Graph Mode (ACLGraph)**: [Experimental]Enhanced full graph mode with GQA support, memory optimizations, unified logic between ACLGraph and Torchair, and improved stability. [#3560](https://github.com/vllm-project/vllm-ascend/pull/3560) [#3970](https://github.com/vllm-project/vllm-ascend/pull/3970) [#3812](https://github.com/vllm-project/vllm-ascend/pull/3812) [#3879](https://github.com/vllm-project/vllm-ascend/pull/3879) [#3888](https://github.com/vllm-project/vllm-ascend/pull/3888) [#3894](https://github.com/vllm-project/vllm-ascend/pull/3894) [#5118](https://github.com/vllm-project/vllm-ascend/pull/5118)
- **Multi-Token Prediction (MTP)**: Significantly improved MTP support with chunked prefill for DeepSeek, quantization support, full graph mode, PCP/DCP integration, and async scheduling. MTP now works in most cases and is recommended for use. [#2711](https://github.com/vllm-project/vllm-ascend/pull/2711) [#2713](https://github.com/vllm-project/vllm-ascend/pull/2713) [#3620](https://github.com/vllm-project/vllm-ascend/pull/3620) [#3845](https://github.com/vllm-project/vllm-ascend/pull/3845) [#3910](https://github.com/vllm-project/vllm-ascend/pull/3910) [#3915](https://github.com/vllm-project/vllm-ascend/pull/3915) [#4102](https://github.com/vllm-project/vllm-ascend/pull/4102) [#4111](https://github.com/vllm-project/vllm-ascend/pull/4111) [#4770](https://github.com/vllm-project/vllm-ascend/pull/4770) [#5477](https://github.com/vllm-project/vllm-ascend/pull/5477)
- **Eagle Speculative Decoding**: Eagle spec decode now works with full graph mode and is more stable. [#5118](https://github.com/vllm-project/vllm-ascend/pull/5118) [#4893](https://github.com/vllm-project/vllm-ascend/pull/4893) [#5804](https://github.com/vllm-project/vllm-ascend/pull/5804)
- **PD Disaggregation**: Set ADXL engine as default backend for disaggregated prefill with improved performance and stability. Added support for KV NZ feature for DeepSeek decode node. [#3761](https://github.com/vllm-project/vllm-ascend/pull/3761) [#3950](https://github.com/vllm-project/vllm-ascend/pull/3950) [#5008](https://github.com/vllm-project/vllm-ascend/pull/5008) [#3072](https://github.com/vllm-project/vllm-ascend/pull/3072)
- **KV Pool & Mooncake**: Enhanced KV pool with Mooncake connector support for PCP/DCP, multiple input suffixes, and improved performance of Layerwise Connector. [#3690](https://github.com/vllm-project/vllm-ascend/pull/3690) [#3752](https://github.com/vllm-project/vllm-ascend/pull/3752) [#3849](https://github.com/vllm-project/vllm-ascend/pull/3849) [#4183](https://github.com/vllm-project/vllm-ascend/pull/4183) [#5303](https://github.com/vllm-project/vllm-ascend/pull/5303)
- **EPLB (Elastic Prefill Load Balancing)**: EPLB is now more stable with many bug fixes. Mix placement now works. [#6086](https://github.com/vllm-project/vllm-ascend/pull/6086)
- **EPLB (Elastic Prefill Load Balancing)**: [Experimental]EPLB is now more stable with many bug fixes. Mix placement now works. [#6086](https://github.com/vllm-project/vllm-ascend/pull/6086)
- **Full Decode Only Mode**: Added support for Qwen3-Next and DeepSeekv32 in full_decode_only mode with bug fixes. [#3949](https://github.com/vllm-project/vllm-ascend/pull/3949) [#3986](https://github.com/vllm-project/vllm-ascend/pull/3986) [#3763](https://github.com/vllm-project/vllm-ascend/pull/3763)
- **Model Runner V2**: Added basic support for Model Runner V2, the next generation of vLLM. It will be used by default in future releases. [#5210](https://github.com/vllm-project/vllm-ascend/pull/5210)
- **Model Runner V2**: [Experimental]Added basic support for Model Runner V2, the next generation of vLLM. It will be used by default in future releases. [#5210](https://github.com/vllm-project/vllm-ascend/pull/5210)
### Features
- **W8A16 Quantization**: Added new W8A16 quantization method support. [#4541](https://github.com/vllm-project/vllm-ascend/pull/4541)
- **UCM Connector**: Added UCMConnector for KV Cache Offloading. [#4411](https://github.com/vllm-project/vllm-ascend/pull/4411)
- **Batch Invariant**: Implemented basic framework for batch invariant feature. [#5517](https://github.com/vllm-project/vllm-ascend/pull/5517)
- **W8A16 Quantization**: [Experimental]Added new W8A16 quantization method support. [#4541](https://github.com/vllm-project/vllm-ascend/pull/4541)
- **UCM Connector**: [Experimental]Added UCMConnector for KV Cache Offloading. [#4411](https://github.com/vllm-project/vllm-ascend/pull/4411)
- **Batch Invariant**: [Experimental]Implemented basic framework for batch invariant feature. [#5517](https://github.com/vllm-project/vllm-ascend/pull/5517)
- **Sampling**: Enhanced sampling with async_scheduler and disable_padded_drafter_batch support in Eagle. [#4893](https://github.com/vllm-project/vllm-ascend/pull/4893)
### Hardware and Operator Support
@@ -53,13 +53,13 @@ This is the final release of v0.13.0 for vLLM Ascend. Please follow the [officia
Many custom ops and triton kernels were added in this release to speed up model performance:
- **DeepSeek Performance**: Improved performance for DeepSeek V3.2 by eliminating HD synchronization in async scheduling and optimizing memory usage for MTP. [#4805](https://github.com/vllm-project/vllm-ascend/pull/4805) [#2713](https://github.com/vllm-project/vllm-ascend/pull/2713)
- **Qwen3-Next Performance**: Improved performance with Triton ops and optimizations. [#5664](https://github.com/vllm-project/vllm-ascend/pull/5664) [#5984](https://github.com/vllm-project/vllm-ascend/pull/5984) [#5765](https://github.com/vllm-project/vllm-ascend/pull/5765)
- **DeepSeek Performance**: [Experimental]Improved performance for DeepSeek V3.2 by eliminating HD synchronization in async scheduling and optimizing memory usage for MTP. [#4805](https://github.com/vllm-project/vllm-ascend/pull/4805) [#2713](https://github.com/vllm-project/vllm-ascend/pull/2713)
- **Qwen3-Next Performance**: [Experimental]Improved performance with Triton ops and optimizations. [#5664](https://github.com/vllm-project/vllm-ascend/pull/5664) [#5984](https://github.com/vllm-project/vllm-ascend/pull/5984) [#5765](https://github.com/vllm-project/vllm-ascend/pull/5765)
- **FlashComm**: Enhanced FlashComm v2 optimization with o_shared linear and communication domain fixes. [#3232](https://github.com/vllm-project/vllm-ascend/pull/3232) [#4188](https://github.com/vllm-project/vllm-ascend/pull/4188) [#4458](https://github.com/vllm-project/vllm-ascend/pull/4458) [#5848](https://github.com/vllm-project/vllm-ascend/pull/5848)
- **MoE Optimization**: Optimized all2allv for MoE models and enhanced all-reduce skipping logic. [#3738](https://github.com/vllm-project/vllm-ascend/pull/3738) [#5329](https://github.com/vllm-project/vllm-ascend/pull/5329)
- **Attention Optimization**: Moved attention update stream out of loop, converted BSND to TND format for long sequence optimization, and removed transpose step after attention switching to transpose_batchmatmul. [#3848](https://github.com/vllm-project/vllm-ascend/pull/3848) [#3778](https://github.com/vllm-project/vllm-ascend/pull/3778) [#5390](https://github.com/vllm-project/vllm-ascend/pull/5390)
- **Quantization Performance**: Moved quantization before allgather in Allgather EP. [#3420](https://github.com/vllm-project/vllm-ascend/pull/3420)
- **Layerwise Connector**: Improved performance of Layerwise Connector. [#5303](https://github.com/vllm-project/vllm-ascend/pull/5303)
- **Layerwise Connector**: [Experimental]Improved performance of Layerwise Connector. [#5303](https://github.com/vllm-project/vllm-ascend/pull/5303)
- **Prefix Cache**: Improved performance of prefix cache features. [#4022](https://github.com/vllm-project/vllm-ascend/pull/4022)
- **Async Scheduling**: Fixed async copy and eliminated hangs in async scheduling. [#4113](https://github.com/vllm-project/vllm-ascend/pull/4113) [#4233](https://github.com/vllm-project/vllm-ascend/pull/4233)
- **Memory Operations**: Removed redundant D2H operations and deleted redundant operations in model_runner. [#4063](https://github.com/vllm-project/vllm-ascend/pull/4063) [#3677](https://github.com/vllm-project/vllm-ascend/pull/3677)