diff --git a/docs/platforms/ascend_npu.md b/docs/platforms/ascend_npu.md
index d91382f65..005132503 100644
--- a/docs/platforms/ascend_npu.md
+++ b/docs/platforms/ascend_npu.md
@@ -11,7 +11,6 @@ You can install SGLang using any of the methods below. Please go through `System
 | Pytorch Adapter   | 7.3.0                   | [link](https://gitcode.com/Ascend/pytorch/releases)                                                                                                                                                                          |
 | MemFabric         | 1.0.5                   | `pip install memfabric-hybrid==1.0.5`                                                                                                                                                                 |
 | Triton            | 3.2.0                   | `pip install triton-ascend`|
-| Bisheng           | 20251121                | [link](https://sglang-ascend.obs.cn-east-3.myhuaweicloud.com/sglang/triton_ascend/Ascend-BiSheng-toolkit_aarch64_20251121.run)                                                                                               |
 | SGLang NPU Kernel | NA                      | [link](https://github.com/sgl-project/sgl-kernel-npu/releases)                                                                                                                                                               |
 
 <a id="obtain-cann-image"></a>
@@ -65,11 +64,6 @@ If you are using other versions of `torch` and install `torch_npu`, check [insta
 
 We provide our own implementation of Triton for Ascend.
 
-```shell
-BISHENG_NAME="Ascend-BiSheng-toolkit_aarch64_20251121.run"
-BISHENG_URL="https://sglang-ascend.obs.cn-east-3.myhuaweicloud.com/sglang/triton_ascend/${BISHENG_NAME}"
-wget -O "${BISHENG_NAME}" "${BISHENG_URL}" && chmod a+x "${BISHENG_NAME}" && "./${BISHENG_NAME}" --install && rm "${BISHENG_NAME}"
-```
 ```shell
 pip install triton-ascend
 ```
@@ -112,8 +106,8 @@ You can download the SGLang image or build an image based on Dockerfile to obtai
 dockerhub: docker.io/lmsysorg/sglang:$tag
 # Main-based tag, change main to specific version like v0.5.6,
 # you can get image for specific version
-Atlas 800I A3 : {main}-cann8.3.rc2-a3
-Atlas 800I A2: {main}-cann8.3.rc2-910b
+Atlas 800I A3 : {main}-cann8.5.0-a3
+Atlas 800I A2: {main}-cann8.5.0-910b
 ```
 2. Build an image based on Dockerfile
 ```shell
diff --git a/docs/platforms/ascend_npu_support_models.md b/docs/platforms/ascend_npu_support_models.md
index 11a7b77c1..4a455d0c6 100644
--- a/docs/platforms/ascend_npu_support_models.md
+++ b/docs/platforms/ascend_npu_support_models.md
@@ -46,7 +46,7 @@ You are welcome to enable various models based on your business requirements.
 | AI-ModelScope/dbrx-instruct                | DBRX (Databricks)              | **<span style="color: green;">√</span>** | **<span style="color: green;">√</span>** |
 | baichuan-inc/Baichuan2-13B-Chat            | Baichuan 2 (7B, 13B)           | **<span style="color: green;">√</span>** | **<span style="color: green;">√</span>** |
 | baidu/ERNIE-4.5-21B-A3B-PT                 | ERNIE-4.5 (4.5, 4.5MoE series) | **<span style="color: green;">√</span>** | **<span style="color: green;">√</span>** |
-| openbmb/MiniCPM3-4B                        | MiniCPM (v3, 4B)               | **<span style="color: green;">√</span>** | **<span style="color: green;">√</span>** |
+| OpenBMB/MiniCPM3-4B                        | MiniCPM (v3, 4B)               | **<span style="color: green;">√</span>** | **<span style="color: green;">√</span>** |
 | Kimi/Kimi-K2-Thinking                      | Kimi                           | **<span style="color: green;">√</span>** | **<span style="color: green;">√</span>** |
 | openai/gpt-oss-120b                        | GPTOSS                         | **<span style="color: green;">√</span>** | **<span style="color: green;">√</span>** |
 
@@ -74,7 +74,7 @@ You are welcome to enable various models based on your business requirements.
 | lmms-lab/llava-onevision-qwen2-7b-ov          | LLaVA-OneVision           | **<span style="color: green;">√</span>** | **<span style="color: green;">√</span>** |
 | Kimi/Kimi-VL-A3B-Instruct                     | Kimi-VL (A3B)             | **<span style="color: green;">√</span>** | **<span style="color: green;">√</span>** |
 | ZhipuAI/GLM-4.5V                              | GLM-4.5V (106B)           | **<span style="color: green;">√</span>** | **<span style="color: green;">√</span>** |
-| meta-llama/Llama-3.2-11B-Vision-Instruct      | Llama 3.2 Vision (11B)    | **<span style="color: green;">√</span>** | **<span style="color: green;">√</span>** |
+| LLM-Research/Llama-3.2-11B-Vision-Instruct    | Llama 3.2 Vision (11B)    | **<span style="color: green;">√</span>** | **<span style="color: green;">√</span>** |
 
 ## Embedding Models
 
@@ -95,7 +95,7 @@ You are welcome to enable various models based on your business requirements.
 | 	Shanghai_AI_Laboratory/internlm2-7b-reward | InternLM 2 Reward         | **<span style="color: green;">√</span>** | **<span style="color: green;">√</span>** |
 | 	Qwen/Qwen2.5-Math-RM-72B                   | Qwen2.5 Reward - Math     | **<span style="color: green;">√</span>** | **<span style="color: green;">√</span>** |
 | 	Howeee/Qwen2.5-1.5B-apeach                 | Qwen2.5 Reward - Sequence | **<span style="color: green;">√</span>** | **<span style="color: green;">√</span>** |
-| 	Skywork/Skywork-Reward-Gemma-2-27B-v0.2    | Gemma 2-27B Reward        | **<span style="color: green;">√</span>** | **<span style="color: green;">√</span>** |
+| 	AI-ModelScope/Skywork-Reward-Gemma-2-27B-v0.2    | Gemma 2-27B Reward  | **<span style="color: green;">√</span>** | **<span style="color: green;">√</span>** |
 
 ## Rerank Models