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【doc】Add model feature matrix (#4950)

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

doc tutorials add  model feature matrix：
DeepSeekR1
DeepSeekV3.1
Qwen3-Dense
Qwen3-Moe
Qwen3-Next
Qwen2.5
Qwen2.5-VL
Qwen3-VL

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

### How was this patch tested?

- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c

---------

Signed-off-by: 1092626063 <1092626063@qq.com>
This commit is contained in:
1092626063
2025-12-12 15:37:39 +08:00
committed by GitHub
parent cf801fdbbb
commit 62a9fea7af
1 changed files with 11 additions and 11 deletions
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docs/source/user_guide/support_matrix/supported_models.md
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@@ -8,16 +8,16 @@ Get the latest info here: https://github.com/vllm-project/vllm-ascend/issues/160
| Model | Support | Note | BF16 | Supported Hardware | W8A8 | Chunked Prefill | Automatic Prefix Cache | LoRA | Speculative Decoding | Async Scheduling | Tensor Parallel | Pipeline Parallel | Expert Parallel | Data Parallel | Prefill-decode Disaggregation | Piecewise AclGraph | Fullgraph AclGraph | max-model-len | MLP Weight Prefetch | Doc |
|-------------------------------|-----------|----------------------------------------------------------------------|------|--------------------|------|-----------------|------------------------|------|----------------------|------------------|-----------------|-------------------|-----------------|---------------|-------------------------------|--------------------|--------------------|---------------|---------------------|-----|
| DeepSeek V3/3.1 | ✅ | |||||||||||||||||||
| DeepSeek V3.2 EXP | ✅ | | ✅ | A2/A3 | ✅ | ✅ | ✅ | ✅ | ✅ | | ✅ | ✅ | ✅ | ✅ | ❌ | | | 163840 | | [DeepSeek-V3.2-Exp tutorial](../../tutorials/DeepSeek-V3.2.md) |
| DeepSeek R1 | ✅ | |||||||||||||||||||
| DeepSeek V3/3.1 | ✅ | | ✅ | A2/A3 | ✅ | ✅ | ✅ || ✅ || ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | 240k || [DeepSeek-V3.1](../../tutorials/DeepSeek-V3.1.md) |
| DeepSeek V3.2 EXP | ✅ | | ✅ | A2/A3 | ✅ | ✅ | ✅ | ✅ | ✅ || ✅ | ✅ | ✅ | ✅ | ❌ ||| 160k || [DeepSeek-V3.2](../../tutorials/DeepSeek-V3.2.md) |
| DeepSeek R1 | ✅ | | ✅ | A2/A3 | ✅ | ✅ | ✅ || ✅ || ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | 128k || [DeepSeek-R1](../../tutorials/DeepSeek-R1.md) |
| DeepSeek Distill (Qwen/Llama) | ✅ | |||||||||||||||||||
| Qwen3 | ✅ | |||||||||||||||||||
| Qwen3 | ✅ | | ✅ | A2/A3 | ✅ | ✅ | ✅ ||| ✅ | ✅ ||| ✅ || ✅ | ✅ | 128k | ✅ | [Qwen3-Dense](../../tutorials/Qwen3-Dense.md) |
| Qwen3-based | ✅ | |||||||||||||||||||
| Qwen3-Coder | ✅ | | A2/A3 |✅||✅|✅|✅|||✅|✅|✅|✅||||||[Qwen3-Coder-30B-A3B tutorial](../../tutorials/Qwen3-Coder-30B-A3B.md)|
| Qwen3-Moe | ✅ | |||||||||||||||||||
| Qwen3-Next | ✅ | |||||||||||||||||||
| Qwen2.5 | ✅ | |||||||||||||||||||
| Qwen3-Coder | ✅ | | ✅ | A2/A3 ||✅|✅|✅|||✅|✅|✅|✅||||||[Qwen3-Coder-30B-A3B tutorial](../../tutorials/Qwen3-Coder-30B-A3B.md)|
| Qwen3-Moe | ✅ | | ✅ | A2/A3 | ✅ | ✅ | ✅ ||| ✅ | ✅ || ✅ | ✅ | ✅ | ✅ | ✅ ||| [Qwen3-235B-A22B](../../tutorials/Qwen3-235B-A22B.md) |
| Qwen3-Next | ✅ | | ✅ | A2/A3 | ✅ |||||| ✅ ||| ✅ || ✅ | ✅ ||| [Qwen3-Next](../../tutorials/Qwen3-Next.md) |
| Qwen2.5 | ✅ | | ✅ | A2/A3 | ✅ | ✅ | ✅ |||| ✅ || ✅ | ✅ |||||| [Qwen2.5-7B](../../tutorials/Qwen2.5-7B.md) |
| Qwen2 | ✅ | |||||||||||||||||||
| Qwen2-based | ✅ | |||||||||||||||||||
| QwQ-32B | ✅ | |||||||||||||||||||
@@ -58,10 +58,10 @@ Get the latest info here: https://github.com/vllm-project/vllm-ascend/issues/160
| Model | Support | Note | BF16 | Supported Hardware | W8A8 | Chunked Prefill | Automatic Prefix Cache | LoRA | Speculative Decoding | Async Scheduling | Tensor Parallel | Pipeline Parallel | Expert Parallel | Data Parallel | Prefill-decode Disaggregation | Piecewise AclGraph | Fullgraph AclGraph | max-model-len | MLP Weight Prefetch | Doc |
|--------------------------------|---------------|----------------------------------------------------------------------|------|--------------------|------|-----------------|------------------------|------|----------------------|------------------|-----------------|-------------------|-----------------|---------------|-------------------------------|--------------------|--------------------|---------------|---------------------|-----|
| Qwen2-VL | ✅ | |||||||||||||||||||
| Qwen2.5-VL | ✅ | |||||||||||||||||||
| Qwen3-VL | ✅ | ||A2/A3|||||||✅|||||✅|✅||||
| Qwen2.5-VL | ✅ | | ✅ | A2/A3 | ✅ | ✅ | ✅ ||| ✅ | ✅ |||| ✅ | ✅ | ✅ | 30k || [Qwen-VL-Dense](../../tutorials/Qwen-VL-Dense.md) |
| Qwen3-VL | ✅ | ||A2/A3|||||||✅|||||✅|✅||| [Qwen-VL-Dense](../../tutorials/Qwen-VL-Dense.md) |
| Qwen3-VL-MOE | ✅ | |||||||||||||||||||
| Qwen2.5-Omni | ✅ | [1760](https://github.com/vllm-project/vllm-ascend/issues/1760) |||||||||||||||||||
| Qwen2.5-Omni | ✅ ||||||||||||||||||| [Qwen2.5-Omni](../../tutorials/Qwen2.5-Omni.md) |
| QVQ | ✅ | |||||||||||||||||||
| LLaVA 1.5/1.6 | ✅ | [1962](https://github.com/vllm-project/vllm-ascend/issues/1962) |||||||||||||||||||
| InternVL2 | ✅ | |||||||||||||||||||