[Doc] Add release note for v0.11.0rc1 (#3931)

Add release note for v0.11.0rc1.


- vLLM version: v0.11.0
- vLLM main:
83f478bb19

Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>

docs/source/community/versioning_policy.md

@@ -22,6 +22,7 @@ The table below is the release compatibility matrix for vLLM Ascend release.
 
 | vLLM Ascend | vLLM         | Python           | Stable CANN | PyTorch/torch_npu  | MindIE Turbo |
 |-------------|--------------|------------------|-------------|--------------------|--------------|
+| v0.11.0rc1  | v0.11.0      | >= 3.9, < 3.12   | 8.3.RC1     | 2.7.1 / 2.7.1            |              |
 | v0.11.0rc0  | v0.11.0rc3      | >= 3.9, < 3.12   | 8.2.RC1     | 2.7.1 / 2.7.1.dev20250724            |              |
 | v0.10.2rc1  | v0.10.2      | >= 3.9, < 3.12   | 8.2.RC1     | 2.7.1 / 2.7.1.dev20250724            |              |
 | v0.10.1rc1  | v0.10.1/v0.10.1.1 | >= 3.9, < 3.12   | 8.2.RC1     | 2.7.1 / 2.7.1.dev20250724            |              |
@@ -49,6 +50,7 @@ For main branch of vLLM Ascend, we usually make it compatible with the latest vL
 
 | Date       | Event                                     |
 |------------|-------------------------------------------|
+| 2025.11.10 | Release candidates, v0.11.0rc1            |
 | 2025.09.30 | Release candidates, v0.11.0rc0            |
 | 2025.09.16 | Release candidates, v0.10.2rc1            |
 | 2025.09.04 | Release candidates, v0.10.1rc1            |

docs/source/conf.py

@@ -65,14 +65,14 @@ myst_substitutions = {
     # the branch of vllm, used in vllm clone
     # - main branch: 'main'
     # - vX.Y.Z branch: 'vX.Y.Z'
-    'vllm_version': 'v0.11.0rc3',
+    'vllm_version': 'v0.11.0',
     # the branch of vllm-ascend, used in vllm-ascend clone and image tag
     # - main branch: 'main'
     # - vX.Y.Z branch: latest vllm-ascend release tag
-    'vllm_ascend_version': 'v0.11.0rc0',
+    'vllm_ascend_version': 'v0.11.0rc1',
     # the newest release version of vllm-ascend and matched vLLM, used in pip install.
     # This value should be updated when cut down release.
-    'pip_vllm_ascend_version': "0.11.0rc0",
+    'pip_vllm_ascend_version': "0.11.0rc1",
     'pip_vllm_version': "0.11.0",
     # CANN image tag
     'cann_image_tag': "8.3.rc1-910b-ubuntu22.04-py3.11",

docs/source/faqs.md

@@ -3,7 +3,7 @@
 ## Version Specific FAQs
 
 - [[v0.9.1] FAQ & Feedback](https://github.com/vllm-project/vllm-ascend/issues/2643)
-- [[v0.11.0rc0] FAQ & Feedback](https://github.com/vllm-project/vllm-ascend/issues/3222)
+- [[v0.11.0rc1] FAQ & Feedback](https://github.com/vllm-project/vllm-ascend/issues/3222)
 
 ## General FAQs
 

docs/source/user_guide/release_notes.md

@@ -1,5 +1,37 @@
 # Release Notes
 
+## v0.11.0rc1 - 2025.11.10
+
+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.
+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.
+
+### Highlights
+- CANN is upgrade to 8.3.RC1. Torch-npu is upgrade to 2.7.1. [#3945](https://github.com/vllm-project/vllm-ascend/pull/3945) [#3896](https://github.com/vllm-project/vllm-ascend/pull/3896)
+- PrefixCache and Chunked Prefill are enabled by default. [#3967](https://github.com/vllm-project/vllm-ascend/pull/3967)
+- W4A4 quantization is supported now. [#3427](https://github.com/vllm-project/vllm-ascend/pull/3427) Official tutorial is available at [here](https://docs.vllm.ai/projects/ascend/en/latest/tutorials/single_npu_qwen3_w4a4.html.
+
+### 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).
+- 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)
+
+### Other
+- Refactor the MOE module to make it clearer and easier to understand and the performance has improved in both quantitative and non-quantitative scenarios.
+- Refactor model register module to make it easier to maintain. We'll remove this module in Q4 2025. [#3004](https://github.com/vllm-project/vllm-ascend/pull/3004)
+- Torchair is deprecated. We'll remove it once the performance of ACL Graph is good enough. The deadline is Q1 2026.
+- LLMDatadist KV Connector is deprecated. We'll remove it in Q1 2026.
+- Refactor the linear module to support features flashcomm1 and flashcomm2 in paper [flashcomm](https://arxiv.org/pdf/2412.04964) [#3004](https://github.com/vllm-project/vllm-ascend/pull/3004) [#3334](https://github.com/vllm-project/vllm-ascend/pull/3334)
+
+### Known issue
+- The memory may be leaked and the service may be stuck after long time serving. This is a bug from torch-npu, we'll upgrade and fix it soon.
+- The accuracy of qwen2.5 VL is not very good. This is a bug lead by CANN, we fix it soon.
+- For long sequence input case, there is no response sometimes and the kv cache usage is become higher. This is a bug for scheduler. We are working on it.
+- Qwen2-audio doesn't work by default, we're fixing it. Temporary solution is to set `--gpu-memory-utilization` to a suitable value, such as 0.8.
+- When running Qwen3-Next with expert parallel enabled, please set `HCCL_BUFFSIZE` environment variable to a suitable value, such as 1024.
+- The accuracy of DeepSeek3.2 with aclgraph is not correct. Temporary solution is to set `cudagraph_capture_sizes` to a suitable value depending on the batch size for the input.
+
 ## v0.11.0rc0 - 2025.09.30
 
 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.