diff --git a/docs_new/cookbook/autoregressive/DeepSeek/DeepSeek-V3.mdx b/docs_new/cookbook/autoregressive/DeepSeek/DeepSeek-V3.mdx
index ace8ac1e6..9c1a32569 100644
--- a/docs_new/cookbook/autoregressive/DeepSeek/DeepSeek-V3.mdx
+++ b/docs_new/cookbook/autoregressive/DeepSeek/DeepSeek-V3.mdx
@@ -425,7 +425,7 @@ For multi-node serving and hardware-specific examples:
 - [16× A100 INT8](https://github.com/sgl-project/sglang/tree/main/benchmark/deepseek_v3#example-serving-with-16-a100a800-with-int8-quantization)
 - [32× L40S INT8](https://github.com/sgl-project/sglang/tree/main/benchmark/deepseek_v3#example-serving-with-32-l40s-with-int8-quantization)
 - [Xeon 6980P CPU](../../../docs/hardware-platforms/cpu_server#example-running-deepseek-r1)
-- [4× Atlas 800I A3 (int8)](../../../docs/hardware-platforms/ascend-npus/ascend_npu_deepseek_example#running-deepseek-with-pd-disaggregation-on-4-x-atlas-800i-a3)
+- [4× Atlas 800I A3 (int8)](../../../docs/hardware-platforms/ascend-npus/model-tutorials/deepseek_r1#multi-node-pd-disaggregation-deployment)
 
 **Blog references for large-scale deployment:**
 
diff --git a/docs_new/docs.json b/docs_new/docs.json
index 6f109dfb9..063f9ab24 100644
--- a/docs_new/docs.json
+++ b/docs_new/docs.json
@@ -435,11 +435,11 @@
     },
     {
       "source": "/platforms/ascend/ascend_npu_best_practice.html",
-      "destination": "/docs/hardware-platforms/ascend-npus/ascend_npu_best_practice"
+      "destination": "/docs/hardware-platforms/ascend-npus/best_practice"
     },
     {
       "source": "/platforms/ascend/ascend_npu_deepseek_example.html",
-      "destination": "/docs/hardware-platforms/ascend-npus/ascend_npu_deepseek_example"
+      "destination": "/docs/hardware-platforms/ascend-npus/model-tutorials/deepseek_v3_2"
     },
     {
       "source": "/platforms/ascend/ascend_npu_environment_variables.html",
@@ -447,7 +447,7 @@
     },
     {
       "source": "/platforms/ascend/ascend_npu_glm5_examples.html",
-      "destination": "/docs/hardware-platforms/ascend-npus/ascend_npu_glm5_examples"
+      "destination": "/docs/hardware-platforms/ascend-npus/model-tutorials/glm_5_1"
     },
     {
       "source": "/platforms/ascend/ascend_npu_quantization.html",
@@ -459,11 +459,11 @@
     },
     {
       "source": "/platforms/ascend/ascend_npu_qwen3_5_examples.html",
-      "destination": "/docs/hardware-platforms/ascend-npus/ascend_npu_qwen3_5_examples"
+      "destination": "/docs/hardware-platforms/ascend-npus/model-tutorials/qwen3_5_397b"
     },
     {
       "source": "/platforms/ascend/ascend_npu_qwen3_examples.html",
-      "destination": "/docs/hardware-platforms/ascend-npus/ascend_npu_qwen3_examples"
+      "destination": "/docs/hardware-platforms/ascend-npus/model-tutorials/qwen3_235b_a22b"
     },
     {
       "source": "/platforms/ascend/ascend_npu_support.html",
@@ -878,6 +878,14 @@
               {
                 "group": "Ascend NPUs",
                 "pages": [
+                  "docs/hardware-platforms/ascend-npus/ascend_npu_quick_start",
+                  "docs/hardware-platforms/ascend-npus/ascend_npu",
+                  "docs/hardware-platforms/ascend-npus/ascend_npu_support_features",
+                  "docs/hardware-platforms/ascend-npus/ascend_npu_support_models",
+                  "docs/hardware-platforms/ascend-npus/ascend_npu_quantization",
+                  "docs/hardware-platforms/ascend-npus/mindspore_backend",
+                  "docs/hardware-platforms/ascend-npus/ascend_contribution_guide",
+                  "docs/hardware-platforms/ascend-npus/ascend_npu_support_new_models",
                   {
                     "group": "Model Tutorials",
                     "pages": [
@@ -896,17 +904,6 @@
                       "docs/hardware-platforms/ascend-npus/model-tutorials/qwen3_next_80b_a3b_instruct"
                     ]
                   },
-                  "docs/hardware-platforms/ascend-npus/ascend_npu_quick_start",
-                  "docs/hardware-platforms/ascend-npus/ascend_npu",
-                  "docs/hardware-platforms/ascend-npus/ascend_npu_support_features",
-                  "docs/hardware-platforms/ascend-npus/ascend_npu_support_models",
-                  "docs/hardware-platforms/ascend-npus/ascend_npu_quantization",
-                  "docs/hardware-platforms/ascend-npus/ascend_npu_deepseek_example",
-                  "docs/hardware-platforms/ascend-npus/ascend_npu_qwen3_examples",
-                  "docs/hardware-platforms/ascend-npus/mindspore_backend",
-                  "docs/hardware-platforms/ascend-npus/ascend_contribution_guide",
-                  "docs/hardware-platforms/ascend-npus/ascend_npu_support_new_models",
-                  "docs/hardware-platforms/ascend-npus/ascend_npu_best_practice",
                   {
                     "group": "Best Practice",
                     "pages": [
@@ -929,8 +926,6 @@
                   "docs/hardware-platforms/ascend-npus/ascend_npu_accuracy_evaluation",
                   "docs/hardware-platforms/ascend-npus/ascend_npu_performance_testing",
                   "docs/hardware-platforms/ascend-npus/ascend_npu_ring_sp_performance",
-                  "docs/hardware-platforms/ascend-npus/ascend_npu_qwen3_5_examples",
-                  "docs/hardware-platforms/ascend-npus/ascend_npu_glm5_examples",
                   "docs/hardware-platforms/ascend-npus/ascend_npu_environment_variables",
                   "docs/hardware-platforms/ascend-npus/ascend_npu_faq",
                   "docs/hardware-platforms/ascend-npus/ascend_npu_operator_performance_optimizing",
diff --git a/docs_new/docs/hardware-platforms/ascend-npus/ascend_npu.mdx b/docs_new/docs/hardware-platforms/ascend-npus/ascend_npu.mdx
index 1616c87ce..ce65bbd2a 100644
--- a/docs_new/docs/hardware-platforms/ascend-npus/ascend_npu.mdx
+++ b/docs_new/docs/hardware-platforms/ascend-npus/ascend_npu.mdx
@@ -41,7 +41,7 @@ You can install SGLang using any of the methods below. Please go through `System
     <tr>
       <td style={{padding: "9px 12px", fontWeight: 500, backgroundColor: "rgba(255,255,255,0.02)"}}>Triton</td>
       <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>3.2.1.dev20260530</td>
-      <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.02)"}}>`pip install triton-ascend==3.2.1.dev20260530 \`<br/>`--extra-index-url=https://mirrors.huaweicloud.com/ascend/repos/pypi/nightly \`<br/>`--trusted-host triton-ascend.osinfra.cn`</td>
+      <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.02)"}}>`pip install triton-ascend==3.2.1.dev20260530 \`<br/>`--extra-index-url=https://mirrors.huaweicloud.com/ascend/repos/pypi/nightly \`<br/>`--trusted-host mirrors.huaweicloud.com`</td>
     </tr>
     <tr>
       <td style={{padding: "9px 12px", fontWeight: 500, backgroundColor: "rgba(255,255,255,0.02)"}}>SGLang NPU Kernel</td>
@@ -143,7 +143,7 @@ We provide our own implementation of Triton for Ascend.
 ```bash Command
 pip install triton-ascend==3.2.1.dev20260530 \
   --extra-index-url=https://mirrors.huaweicloud.com/ascend/repos/pypi/nightly \
-  --trusted-host triton-ascend.osinfra.cn
+  --trusted-host mirrors.huaweicloud.com
 ```
 For installation of Triton on Ascend nightly builds or from sources, follow [installation guide](https://gitcode.com/Ascend/triton-ascend/blob/master/docs/sources/getting-started/installation.md)
 
@@ -185,7 +185,7 @@ Ensure sufficient disk space before pulling images. Each Docker image requires a
 1. Download SGLang image
 
 <Tip>
-We publish both **stable releases** and **daily builds**. Choose a stable release tag (e.g., `v0.5.10-npu.rc1-a3`) if you prefer a validated version, or a daily build tag (e.g., `main-cann9.0.0-a3`) if you need the latest development changes.
+We publish both **stable releases** and **daily builds**. Choose a stable release tag (e.g., `v0.5.13.post1-cann9.0.0-a3`) if you prefer a validated version, or a daily build tag (e.g., `main-cann9.0.0-a3`) if you need the latest development changes.
 </Tip>
 
 <Tabs>
@@ -193,7 +193,7 @@ We publish both **stable releases** and **daily builds**. Choose a stable releas
 
 ```bash Command
 # Stable release
-docker pull quay.io/ascend/sglang:v0.5.10-npu.rc1-a3
+docker pull quay.io/ascend/sglang:v0.5.13.post1-cann9.0.0-a3
 
 # Daily build
 docker pull quay.io/ascend/sglang:main-cann9.0.0-a3
@@ -204,7 +204,7 @@ docker pull quay.io/ascend/sglang:main-cann9.0.0-a3
 
 ```bash Command
 # Stable release
-docker pull quay.io/ascend/sglang:v0.5.10-npu.rc1-910b
+docker pull quay.io/ascend/sglang:v0.5.13.post1-cann9.0.0-910b
 
 # Daily build
 docker pull quay.io/ascend/sglang:main-cann9.0.0-910b
diff --git a/docs_new/docs/hardware-platforms/ascend-npus/ascend_npu_accuracy_evaluation.mdx b/docs_new/docs/hardware-platforms/ascend-npus/ascend_npu_accuracy_evaluation.mdx
index 8a6d69d41..110315a62 100644
--- a/docs_new/docs/hardware-platforms/ascend-npus/ascend_npu_accuracy_evaluation.mdx
+++ b/docs_new/docs/hardware-platforms/ascend-npus/ascend_npu_accuracy_evaluation.mdx
@@ -26,7 +26,7 @@ First, launch the SGLang environment using the provided container image:
   <Tab title="Atlas 800I A3">
 
 ```shell Command
-export IMAGE=quay.io/ascend/sglang:v0.5.10-npu.rc1-a3
+export IMAGE=quay.io/ascend/sglang:v0.5.13.post1-cann9.0.0-a3
 
 docker run -it --rm --privileged --network=host --ipc=host --shm-size=16g \
     --device=/dev/davinci0 --device=/dev/davinci1 --device=/dev/davinci2 --device=/dev/davinci3 \
@@ -49,7 +49,7 @@ docker run -it --rm --privileged --network=host --ipc=host --shm-size=16g \
   <Tab title="Atlas 800I A2">
 
 ```shell Command
-export IMAGE=quay.io/ascend/sglang:v0.5.10-npu.rc1-910b
+export IMAGE=quay.io/ascend/sglang:v0.5.13.post1-cann9.0.0-910b
 
 docker run -it --rm --privileged --network=host --ipc=host --shm-size=16g \
     --device=/dev/davinci0 --device=/dev/davinci1 --device=/dev/davinci2 --device=/dev/davinci3 \
diff --git a/docs_new/docs/hardware-platforms/ascend-npus/ascend_npu_faq.mdx b/docs_new/docs/hardware-platforms/ascend-npus/ascend_npu_faq.mdx
index d60cf4f09..c0fab4ab9 100644
--- a/docs_new/docs/hardware-platforms/ascend-npus/ascend_npu_faq.mdx
+++ b/docs_new/docs/hardware-platforms/ascend-npus/ascend_npu_faq.mdx
@@ -293,7 +293,7 @@ Replace model weights, e.g., switch Qwen/Qwen3.5-27B-FP8 to Eco-Tech/Qwen3.5-27B
 
 Docker images for Ascend NPU are available in two types:
 
-- **Stable release** — validated version with a specific tag, e.g., `quay.io/ascend/sglang:v0.5.10-npu.rc1-a3`.
+- **Stable release** — validated version with a specific tag, e.g., `quay.io/ascend/sglang:v0.5.13.post1-cann9.0.0-a3`.
   Recommended for production deployments.
 - **Daily build** — includes the latest development changes, e.g., `quay.io/ascend/sglang:main-cann8.5.0-a3`. Use this
   if you need the latest features or bug fixes that have not yet been included in a stable release.
diff --git a/docs_new/docs/hardware-platforms/ascend-npus/ascend_npu_optimization.mdx b/docs_new/docs/hardware-platforms/ascend-npus/ascend_npu_optimization.mdx
index a560614e0..c3ae0204c 100644
--- a/docs_new/docs/hardware-platforms/ascend-npus/ascend_npu_optimization.mdx
+++ b/docs_new/docs/hardware-platforms/ascend-npus/ascend_npu_optimization.mdx
@@ -5,9 +5,9 @@ metatags:
 ---
 
 This guide explains the role of each parameter used in SGLang deployments on Ascend NPU. It uses
-the [DeepSeek-V3.2 best practice configuration](/docs/hardware-platforms/ascend-npus/ascend_npu_best_practice#deepseek-v3-2-128k-1k-26ms-on-a3-32-cards-disaggregation-mode)
+the [DeepSeek-V3.2 best practice configuration](/docs/hardware-platforms/ascend-npus/best_practice/deepseek_v3_2#pd-disaggregation)
 as the reference example. For a complete list of tested deployment configurations, see the
-[Ascend NPU Best Practice](/docs/hardware-platforms/ascend-npus/ascend_npu_best_practice) page.
+[Ascend NPU Best Practice](/docs/hardware-platforms/ascend-npus/best_practice) page.
 
 <Note>
   Parameters in this guide fall into two categories:
@@ -794,7 +794,7 @@ Casts model weight tensors to the Ascend NPU ACL FRACTAL_NZ format (format 29) f
 
 ## See Also
 
-- [Ascend NPU Best Practice](/docs/hardware-platforms/ascend-npus/ascend_npu_best_practice) — Complete deployment configurations and benchmark results for all supported models
+- [Ascend NPU Best Practice](/docs/hardware-platforms/ascend-npus/best_practice) — Complete deployment configurations and benchmark results for all supported models
 - [Ascend NPU Environment Variables](/docs/hardware-platforms/ascend-npus/ascend_npu_environment_variables) — Reference for all Ascend NPU-related environment variables
 - [DeepSeek V3.2 Guide](/cookbook/autoregressive/DeepSeek/DeepSeek-V3_2) — Detailed usage guide for DeepSeek V3.2 deployment
 - [Expert Parallelism](/docs/advanced_features/expert_parallelism) — DeepEP configuration and tuning guide
diff --git a/docs_new/docs/hardware-platforms/ascend-npus/best_practice/deepseek_r1.mdx b/docs_new/docs/hardware-platforms/ascend-npus/best_practice/deepseek_r1.mdx
index 76d3c218d..403858448 100644
--- a/docs_new/docs/hardware-platforms/ascend-npus/best_practice/deepseek_r1.mdx
+++ b/docs_new/docs/hardware-platforms/ascend-npus/best_practice/deepseek_r1.mdx
@@ -25,8 +25,6 @@ This guide describes the best practice data for DeepSeek-R1 on the Ascend NPU.
 
 ## Optimal Configuration
 
-<a id="pd-disaggregation" title="Referenced by external docs. Verify before removing."></a>
-
 ### DeepSeek-R1 W4A8 1P1D 16P IN3K5 OUT1K5 41ms
 
 **Model**: DeepSeek-R1
@@ -325,6 +323,8 @@ python -m sglang.bench_serving \
     --random-range-ratio 1
 ```
 
+<a id="pd-disaggregation" title="Referenced by external docs. Verify before removing."></a>
+
 ### DeepSeek-R1 W8A8 2P1D 32P IN3K5 OUT1K5 18.9ms
 
 **Model**: DeepSeek-R1
diff --git a/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/deepseek_r1.mdx b/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/deepseek_r1.mdx
index 9e04d522a..e19d51ba4 100644
--- a/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/deepseek_r1.mdx
+++ b/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/deepseek_r1.mdx
@@ -151,14 +151,14 @@ quay.io/ascend/sglang:v0.5.13.post1-cann9.0.0-910b
 Single-node deployment completes both prefill and decode within the same node (PD mixed mode), suitable for scenarios
 with limited hardware resources. This scenario is already covered in the best practice. For the complete, optimized
 deployment commands and benchmark data, see
-[DeepSeek-R1 Best Practice — W4A8 8P PD Mixed On A3](/docs/hardware-platforms/ascend-npus/best_practice/deepseek_r1#w4a8-8p-pd-mixed).
+[DeepSeek-R1 Best Practice — W4A8 8P PD Mixed On A3](/docs/hardware-platforms/ascend-npus/best_practice/deepseek_r1#single-node-pd-mixed).
 
 ### Multi-node PD disaggregation deployment
 
 PD disaggregation splits the prefill and decode stages onto separate nodes, reducing interference and improving
 throughput for high-concurrency scenarios. This scenario is already covered in the best practice. For the complete, optimized
 deployment commands and benchmark data, see
-[DeepSeek-R1 Best Practice — W4A8 16P PD Disaggregation On A3](/docs/hardware-platforms/ascend-npus/best_practice/deepseek_r1#w4a8-16p-pd-disaggregation).
+[DeepSeek-R1 Best Practice — W8A8 32P PD Disaggregation On A3](/docs/hardware-platforms/ascend-npus/best_practice/deepseek_r1#pd-disaggregation).
 
 ## Functional verification
 
diff --git a/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/kimi_k2_6.mdx b/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/kimi_k2_6.mdx
index 039308a12..dd82ad300 100644
--- a/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/kimi_k2_6.mdx
+++ b/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/kimi_k2_6.mdx
@@ -155,7 +155,7 @@ quay.io/ascend/sglang:v0.5.13.post1-cann9.0.0-910b
 Single-node deployment completes both prefill and decode within the same node (PD mixed mode), suitable for scenarios
 with limited hardware resources. This scenario is already covered in the best practice. For the complete, optimized
 deployment commands and benchmark data, see
-[Kimi K2.6 Best Practice — PD Mixed On A3](/docs/hardware-platforms/ascend-npus/best_practice/kimi_k2_6#single-node).
+[Kimi K2.6 Best Practice — PD Mixed On A3](/docs/hardware-platforms/ascend-npus/best_practice/kimi_k2_6#single-node-pd-mixed).
 
 ### Multi-node online deployment
 
@@ -163,7 +163,7 @@ Multi-node deployment distributes the model across multiple Atlas 800I A3 nodes
 prefill and decode on the same nodes (PD mixed mode), suitable for scenarios that need more device memory than a single
 node can provide. This scenario is already covered in the best practice. For the complete, optimized
 deployment commands and benchmark data, see
-[Kimi-K2.6 Best Practice — Multi-node On A3](/docs/hardware-platforms/ascend-npus/best_practice/kimi_k2_6#multi-node).
+[Kimi-K2.6 Best Practice — Multi-node On A3](/docs/hardware-platforms/ascend-npus/best_practice/kimi_k2_6#multi-node-pd-mixed).
 
 ### Multi-node PD disaggregation deployment
 
diff --git a/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/minimax_m2_5.mdx b/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/minimax_m2_5.mdx
index 57841612f..dcd713130 100644
--- a/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/minimax_m2_5.mdx
+++ b/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/minimax_m2_5.mdx
@@ -149,14 +149,7 @@ quay.io/ascend/sglang:v0.5.13.post1-cann9.0.0-910b
 Single-node deployment completes both prefill and decode within the same node (PD mixed mode), suitable for scenarios
 with limited hardware resources. This scenario is already covered in the best practice. For the complete, optimized
 deployment commands and benchmark data, see
-[MiniMax-M2.5 Best Practice — PD Mixed On A3](/docs/hardware-platforms/ascend-npus/best_practice/minimax_m2_5#single-node).
-
-### Multi-node PD disaggregation deployment
-
-PD disaggregation splits the prefill and decode stages onto separate nodes, reducing interference and improving
-throughput for high-concurrency scenarios. This scenario is already covered in the best practice. For the complete, optimized
-deployment commands and benchmark data, see
-[MiniMax-M2.5 Best Practice — PD Disaggregation On A3](/docs/hardware-platforms/ascend-npus/best_practice/minimax_m2_5#pd-disaggregation).
+[MiniMax-M2.5 Best Practice — PD Mixed On A3](/docs/hardware-platforms/ascend-npus/best_practice/minimax_m2_5#single-node-pd-mixed).
 
 ## Functional verification
 
diff --git a/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/qwen3-8b.mdx b/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/qwen3-8b.mdx
index e22e6554c..83f911359 100644
--- a/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/qwen3-8b.mdx
+++ b/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/qwen3-8b.mdx
@@ -147,7 +147,7 @@ quay.io/ascend/sglang:v0.5.13.post1-cann9.0.0-910b
 Single-node deployment completes both prefill and decode within the same node (PD mixed mode), suitable for scenarios
 with limited hardware resources. This scenario is already covered in the best practice. For the complete, optimized
 deployment commands and benchmark data, see
-[Qwen3-8B Best Practice — PD Mixed On A3](/docs/hardware-platforms/ascend-npus/best_practice/qwen3-8b#single-node).
+[Qwen3-8B Best Practice — PD Mixed On A3](/docs/hardware-platforms/ascend-npus/best_practice/qwen3-8b#single-node-pd-mixed).
 
 ## Functional verification
 
diff --git a/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/qwen3_235b_a22b.mdx b/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/qwen3_235b_a22b.mdx
index 2a3100813..db57d9719 100644
--- a/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/qwen3_235b_a22b.mdx
+++ b/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/qwen3_235b_a22b.mdx
@@ -153,7 +153,7 @@ quay.io/ascend/sglang:v0.5.13.post1-cann9.0.0-910b
 Single-node deployment completes both prefill and decode within the same node (PD mixed mode), suitable for scenarios
 with limited hardware resources. This scenario is already covered in the best practice. For the complete, optimized
 deployment commands and benchmark data, see
-[Qwen3-235B-A22B Best Practice — PD Mixed On A3](/docs/hardware-platforms/ascend-npus/best_practice/qwen3_235b_a22b#single-node).
+[Qwen3-235B-A22B Best Practice — PD Mixed On A3](/docs/hardware-platforms/ascend-npus/best_practice/qwen3_235b_a22b#single-node-pd-mixed).
 
 ### Multi-node PD disaggregation deployment
 
diff --git a/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/qwen3_30b_a3b.mdx b/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/qwen3_30b_a3b.mdx
index bbf252816..7db7396c9 100644
--- a/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/qwen3_30b_a3b.mdx
+++ b/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/qwen3_30b_a3b.mdx
@@ -147,7 +147,7 @@ quay.io/ascend/sglang:v0.5.13.post1-cann9.0.0-910b
 Single-node deployment completes both prefill and decode within the same node (PD mixed mode), suitable for scenarios
 with limited hardware resources. This scenario is already covered in the best practice. For the complete, optimized
 deployment commands and benchmark data, see
-[Qwen3-30B-A3B Best Practice — PD Mixed On A3](/docs/hardware-platforms/ascend-npus/best_practice/qwen3_30b_a3b#single-node).
+[Qwen3-30B-A3B Best Practice — PD Mixed On A3](/docs/hardware-platforms/ascend-npus/best_practice/qwen3_30b_a3b#single-node-pd-mixed).
 
 ## Functional verification
 
diff --git a/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/qwen3_32b.mdx b/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/qwen3_32b.mdx
index dc85ce4b2..20cc54c59 100644
--- a/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/qwen3_32b.mdx
+++ b/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/qwen3_32b.mdx
@@ -145,7 +145,7 @@ quay.io/ascend/sglang:v0.5.13.post1-cann9.0.0-910b
 Single-node deployment completes both prefill and decode within the same node (PD mixed mode), suitable for scenarios
 with limited hardware resources. This scenario is already covered in the best practice. For the complete, optimized
 deployment commands and benchmark data, see
-[Qwen3-32B Best Practice — PD Mixed On A3](/docs/hardware-platforms/ascend-npus/best_practice/qwen3_32b#single-node).
+[Qwen3-32B Best Practice — PD Mixed On A3](/docs/hardware-platforms/ascend-npus/best_practice/qwen3_32b#single-node-pd-mixed).
 
 ## Functional verification
 
diff --git a/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/qwen3_5_397b.mdx b/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/qwen3_5_397b.mdx
index 70b6a7d23..3c59571ab 100644
--- a/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/qwen3_5_397b.mdx
+++ b/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/qwen3_5_397b.mdx
@@ -148,7 +148,7 @@ quay.io/ascend/sglang:v0.5.13.post1-cann9.0.0-910b
 Single-node deployment completes both prefill and decode within the same node (PD mixed mode), suitable for scenarios
 with limited hardware resources. This scenario is already covered in the best practice. For the complete, optimized
 deployment commands and benchmark data, see
-[Qwen3.5-397B Best Practice — PD Mixed On A3](/docs/hardware-platforms/ascend-npus/best_practice/qwen3_5_397b#single-node).
+[Qwen3.5-397B Best Practice — PD Mixed On A3](/docs/hardware-platforms/ascend-npus/best_practice/qwen3_5_397b#single-node-pd-mixed).
 
 ## Functional verification
 
diff --git a/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/qwen3_6_27b.mdx b/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/qwen3_6_27b.mdx
index e4b01fb7c..3656c88e2 100644
--- a/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/qwen3_6_27b.mdx
+++ b/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/qwen3_6_27b.mdx
@@ -145,7 +145,7 @@ quay.io/ascend/sglang:v0.5.13.post1-cann9.0.0-910b
 Single-node deployment completes both prefill and decode within the same node (PD mixed mode), suitable for scenarios
 with limited hardware resources. This scenario is already covered in the best practice. For the complete, optimized
 deployment commands and benchmark data, see
-[Qwen3.6-27B Best Practice — PD Mixed On A3](/docs/hardware-platforms/ascend-npus/best_practice/qwen3_6_27b#single-node).
+[Qwen3.6-27B Best Practice — PD Mixed On A3](/docs/hardware-platforms/ascend-npus/best_practice/qwen3_6_27b#single-node-pd-mixed).
 
 ## Functional verification
 
diff --git a/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/qwen3_6_35b_a3b.mdx b/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/qwen3_6_35b_a3b.mdx
index 84bb2d9a5..a766ee11f 100644
--- a/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/qwen3_6_35b_a3b.mdx
+++ b/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/qwen3_6_35b_a3b.mdx
@@ -145,7 +145,7 @@ quay.io/ascend/sglang:v0.5.13.post1-cann9.0.0-910b
 Single-node deployment completes both prefill and decode within the same node (PD mixed mode), suitable for scenarios
 with limited hardware resources. This scenario is already covered in the best practice. For the complete, optimized
 deployment commands and benchmark data, see
-[Qwen3.6-35B-A3B Best Practice — PD Mixed On A3](/docs/hardware-platforms/ascend-npus/best_practice/qwen3_6_35b_a3b#single-node).
+[Qwen3.6-35B-A3B Best Practice — PD Mixed On A3](/docs/hardware-platforms/ascend-npus/best_practice/qwen3_6_35b_a3b#single-node-pd-mixed).
 
 ## Functional verification
 
diff --git a/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/qwen3_next_80b_a3b_instruct.mdx b/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/qwen3_next_80b_a3b_instruct.mdx
index eaf324817..829670080 100644
--- a/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/qwen3_next_80b_a3b_instruct.mdx
+++ b/docs_new/docs/hardware-platforms/ascend-npus/model-tutorials/qwen3_next_80b_a3b_instruct.mdx
@@ -152,7 +152,7 @@ quay.io/ascend/sglang:v0.5.13.post1-cann9.0.0-910b
 Single-node deployment completes both prefill and decode within the same node (PD mixed mode), suitable for scenarios
 with limited hardware resources. This scenario is already covered in the best practice. For the complete, optimized
 deployment commands and benchmark data, see
-[Qwen3-Next-80B-A3B-Instruct Best Practice — PD Mixed On A3](/docs/hardware-platforms/ascend-npus/best_practice/qwen3_next_80b_a3b_instruct#single-node).
+[Qwen3-Next-80B-A3B-Instruct Best Practice — PD Mixed On A3](/docs/hardware-platforms/ascend-npus/best_practice/qwen3_next_80b_a3b_instruct#single-node-pd-mixed).
 
 ## Functional verification