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[Doc] Update tutorial index (#4920)

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Update tutorial index and remove useless doc

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

Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
This commit is contained in:
wangxiyuan
2025-12-11 20:53:13 +08:00
committed by GitHub
parent e56dba9b0d
commit e538fa6f9c
29 changed files with 41 additions and 1034 deletions
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2
docs/source/user_guide/release_notes.md
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@@ -56,7 +56,7 @@ v0.11.0 will be the next official release version of vLLM Ascend. We'll release
### Core
- Performance of Qwen3 and Deepseek V3 series models are improved.
- Mooncake layerwise connector is supported now [#2602](https://github.com/vllm-project/vllm-ascend/pull/2602). Find tutorial [here](https://docs.vllm.ai/projects/ascend/en/latest/tutorials/multi_node_pd_disaggregation_mooncake.html).
- Mooncake layerwise connector is supported now [#2602](https://github.com/vllm-project/vllm-ascend/pull/2602). Find tutorial [here](https://docs.vllm.ai/projects/ascend/en/latest/tutorials/pd_disaggregation_mooncake_multi_node.html).
- MTP > 1 is supported now. [#2708](https://github.com/vllm-project/vllm-ascend/pull/2708)
- [Experimental] Graph mode `FULL_DECODE_ONLY` is supported now! And `FULL` will be landing in the next few weeks. [#2128](https://github.com/vllm-project/vllm-ascend/pull/2128)
- Pooling models, such as bge-m3, are supported now. [#3171](https://github.com/vllm-project/vllm-ascend/pull/3171)

2
docs/source/user_guide/support_matrix/supported_models.md
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@@ -9,7 +9,7 @@ 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-Exp.md) |
| DeepSeek V3.2 EXP | ✅ | | ✅ | A2/A3 | ✅ | ✅ | ✅ | ✅ | ✅ | | ✅ | ✅ | ✅ | ✅ | ❌ | | | 163840 | | [DeepSeek-V3.2-Exp tutorial](../../tutorials/DeepSeek-V3.2.md) |
| DeepSeek R1 | ✅ | |||||||||||||||||||
| DeepSeek Distill (Qwen/Llama) | ✅ | |||||||||||||||||||
| Qwen3 | ✅ | |||||||||||||||||||