[NPU] update best practicce docs from testcase (#29492)

docs_new/docs.json

@@ -917,6 +917,7 @@
                       "docs/hardware-platforms/ascend-npus/best_practice/glm5_1",
                       "docs/hardware-platforms/ascend-npus/best_practice/kimi_k2_6",
                       "docs/hardware-platforms/ascend-npus/best_practice/minimax_m2_5",
+                      "docs/hardware-platforms/ascend-npus/best_practice/mimo_v2_flash",
                       "docs/hardware-platforms/ascend-npus/best_practice/qwen3-8b",
                       "docs/hardware-platforms/ascend-npus/best_practice/qwen3_32b",
                       "docs/hardware-platforms/ascend-npus/best_practice/qwen3_30b_a3b",

docs_new/docs/hardware-platforms/ascend-npus/best_practice/deepseek_r1.mdx

@@ -12,7 +12,7 @@ This page focuses on optimal configuration and benchmark results for DeepSeek-R1
 
 | Model | Hardware | Cards | Deploy Mode | Dataset | TPOT | Quantization | Configuration |
 | --- | --- | --- | --- | --- | --- | --- | --- |
-| DeepSeek-R1 | Atlas 800I A3 | 32 | PD Disaggregation | 3.5K+1.5K | 18.9ms | W8A8 INT8 | [Optimal Configuration](#deepseek-r1-w8a8-2p1d-32p-in3k5-out1k5-18-9ms) |
+| DeepSeek-R1 | Atlas 800I A3 | 32 | PD Disaggregation | 3.5K+1.5K | 16ms | W8A8 INT8 | [Optimal Configuration](#deepseek-r1-w8a8-2p1d-32p-in3k5-out1k5-16ms) |
 | DeepSeek-R1 | Atlas 800I A3 | 32 | PD Disaggregation | 3.5K+1K | 19.0ms | W8A8 INT8 | [Optimal Configuration](#deepseek-r1-w8a8-2p1d-32p-in3k5-out1k-19-0ms) |
 | DeepSeek-R1 | Atlas 800I A3 | 32 | PD Disaggregation | 3.9K+1K | 19.0ms | W8A8 INT8 | [Optimal Configuration](#deepseek-r1-w8a8-2p1d-32p-in3k9-out1k-19-0ms) |
 | DeepSeek-R1 | Atlas 800I A3 | 32 | PD Disaggregation | 6K+1.6K | 20.5ms | W8A8 INT8 | [Optimal Configuration](#deepseek-r1-w8a8-2p1d-32p-in6k-out1k6-20-5ms) |
@@ -21,13 +21,13 @@ This page focuses on optimal configuration and benchmark results for DeepSeek-R1
 
 | Model | Hardware | Cards | Deploy Mode | Dataset | TPOT | Quantization | Configuration |
 | --- | --- | --- | --- | --- | --- | --- | --- |
-| DeepSeek-R1 | Atlas 800I A3 | 16 | PD Disaggregation | 3.5K+1.5K | 41ms | W4A8 INT8 | [Optimal Configuration](#deepseek-r1-w4a8-1p1d-16p-in3k5-out1k5-41ms) |
+| DeepSeek-R1 | Atlas 800I A3 | 16 | PD Disaggregation | 3.5K+1.5K | 50ms | W4A8 INT8 | [Optimal Configuration](#deepseek-r1-w4a8-1p1d-16p-in3k5-out1k5-50ms) |
-| DeepSeek-R1 | Atlas 800I A3 | 8 | PD Mixed | 3.5K+1.5K | 50.36ms | W4A8 INT8 | [Optimal Configuration](#deepseek-r1-w4a8-8p-in3k5-out1k5-50-36ms) |
+| DeepSeek-R1 | Atlas 800I A3 | 8 | PD Mixed | 3.5K+1.5K | 50ms | W4A8 INT8 | [Optimal Configuration](#deepseek-r1-w4a8-8p-in3k5-out1k5-50ms) |
 | DeepSeek-R1 | Atlas 800I A3 | 32 | PD Disaggregation | 3.5K+1.5K | 50ms | W8A8 INT8 | [Optimal Configuration](#deepseek-r1-w8a8-2p1d-32p-in3k5-out1k5-50ms) |
 
 ## Optimal Configuration
 
-### DeepSeek-R1 W4A8 1P1D 16P IN3K5 OUT1K5 41ms
+### DeepSeek-R1 W4A8 1P1D 16P IN3K5 OUT1K5 50ms
 
 **Model**: DeepSeek-R1
 
@@ -41,7 +41,7 @@ This page focuses on optimal configuration and benchmark results for DeepSeek-R1
 
 **Dataset**: 3.5K+1.5K
 
-**TPOT**: 41ms
+**TPOT**: 50ms
 
 #### Model Deployment
 
@@ -127,6 +127,8 @@ do
         --enable-dp-attention \
         --disable-shared-experts-fusion \
         --dtype bfloat16 \
+        --reasoning-parser deepseek-r1 \
+        --tool-call-parser deepseekv3 \
         --disaggregation-transfer-backend ascend \
         --trust-remote-code \
         --attention-backend ascend \
@@ -177,6 +179,8 @@ do
         --dtype bfloat16 \
         --tokenizer-worker-num 4 \
         --load-balance-method round_robin \
+        --reasoning-parser deepseek-r1 \
+        --tool-call-parser deepseekv3 \
         --disaggregation-transfer-backend ascend \
         --trust-remote-code \
         --attention-backend ascend \
@@ -223,7 +227,7 @@ python -m sglang.bench_serving \
 
 <a id="single-node-pd-mixed" title="Referenced by external docs. Verify before removing."></a>
 
-### DeepSeek-R1 W4A8 8P IN3K5 OUT1K5 50.36ms
+### DeepSeek-R1 W4A8 8P IN3K5 OUT1K5 50ms
 
 **Model**: DeepSeek-R1
 
@@ -237,7 +241,7 @@ python -m sglang.bench_serving \
 
 **Dataset**: 3.5K+1.5K
 
-**TPOT**: 50.36ms
+**TPOT**: 50ms
 
 #### Model Deployment
 
@@ -305,7 +309,9 @@ python3 -m sglang.launch_server \
     --speculative-num-steps 3 \
     --speculative-eagle-topk 1 \
     --speculative-num-draft-tokens 4 \
-    --dtype bfloat16
+    --dtype bfloat16 \
+    --reasoning-parser deepseek-r1 \
+    --tool-call-parser deepseekv3
 ```
 
 #### Benchmark
@@ -327,7 +333,7 @@ python -m sglang.bench_serving \
 
 <a id="pd-disaggregation" title="Referenced by external docs. Verify before removing."></a>
 
-### DeepSeek-R1 W8A8 2P1D 32P IN3K5 OUT1K5 18.9ms
+### DeepSeek-R1 W8A8 2P1D 32P IN3K5 OUT1K5 16ms
 
 **Model**: DeepSeek-R1
 
@@ -341,7 +347,7 @@ python -m sglang.bench_serving \
 
 **Dataset**: 3.5K+1.5K
 
-**TPOT**: 18.9ms
+**TPOT**: 16ms
 
 #### Model Deployment
 
@@ -427,6 +433,8 @@ do
         --disable-shared-experts-fusion \
         --dtype bfloat16 \
         --enable-attn-tp-input-scattered \
+        --reasoning-parser deepseek-r1 \
+        --tool-call-parser deepseekv3 \
         --disaggregation-transfer-backend ascend \
         --trust-remote-code \
         --attention-backend ascend \
@@ -481,6 +489,8 @@ do
         --disable-shared-experts-fusion \
         --dtype bfloat16 \
         --load-balance-method round_robin \
+        --reasoning-parser deepseek-r1 \
+        --tool-call-parser deepseekv3 \
         --disaggregation-transfer-backend ascend \
         --trust-remote-code \
         --attention-backend ascend \
@@ -632,6 +642,8 @@ do
         --disable-shared-experts-fusion \
         --dtype bfloat16 \
         --enable-attn-tp-input-scattered \
+        --reasoning-parser deepseek-r1 \
+        --tool-call-parser deepseekv3 \
         --disaggregation-transfer-backend ascend \
         --trust-remote-code \
         --attention-backend ascend \
@@ -686,6 +698,8 @@ do
         --disable-shared-experts-fusion \
         --dtype bfloat16 \
         --load-balance-method round_robin \
+        --reasoning-parser deepseek-r1 \
+        --tool-call-parser deepseekv3 \
         --disaggregation-transfer-backend ascend \
         --trust-remote-code \
         --attention-backend ascend \
@@ -833,6 +847,8 @@ do
         --disable-shared-experts-fusion \
         --dtype bfloat16 \
         --enable-attn-tp-input-scattered \
+        --reasoning-parser deepseek-r1 \
+        --tool-call-parser deepseekv3 \
         --disaggregation-transfer-backend ascend \
         --trust-remote-code \
         --attention-backend ascend \
@@ -887,6 +903,8 @@ do
         --disable-shared-experts-fusion \
         --dtype bfloat16 \
         --load-balance-method round_robin \
+        --reasoning-parser deepseek-r1 \
+        --tool-call-parser deepseekv3 \
         --disaggregation-transfer-backend ascend \
         --trust-remote-code \
         --attention-backend ascend \
@@ -1034,6 +1052,8 @@ do
         --disable-shared-experts-fusion \
         --dtype bfloat16 \
         --enable-attn-tp-input-scattered \
+        --reasoning-parser deepseek-r1 \
+        --tool-call-parser deepseekv3 \
         --disaggregation-transfer-backend ascend \
         --trust-remote-code \
         --attention-backend ascend \
@@ -1088,6 +1108,8 @@ do
         --disable-shared-experts-fusion \
         --dtype bfloat16 \
         --load-balance-method round_robin \
+        --reasoning-parser deepseek-r1 \
+        --tool-call-parser deepseekv3 \
         --disaggregation-transfer-backend ascend \
         --trust-remote-code \
         --attention-backend ascend \
@@ -1234,6 +1256,8 @@ do
         --disable-shared-experts-fusion \
         --dtype bfloat16 \
         --enable-attn-tp-input-scattered \
+        --reasoning-parser deepseek-r1 \
+        --tool-call-parser deepseekv3 \
         --disaggregation-transfer-backend ascend \
         --trust-remote-code \
         --attention-backend ascend \
@@ -1287,6 +1311,8 @@ do
         --disable-shared-experts-fusion \
         --dtype bfloat16 \
         --load-balance-method round_robin \
+        --reasoning-parser deepseek-r1 \
+        --tool-call-parser deepseekv3 \
         --disaggregation-transfer-backend ascend \
         --trust-remote-code \
         --attention-backend ascend \

docs_new/docs/hardware-platforms/ascend-npus/best_practice/deepseek_v3_2.mdx

@@ -125,6 +125,8 @@ do
         --speculative-num-steps 1 \
         --speculative-eagle-topk 1 \
         --speculative-num-draft-tokens 2 \
+        --reasoning-parser deepseek-v3 \
+        --tool-call-parser deepseekv32 \
         --trust-remote-code \
         --attention-backend ascend \
         --device npu
@@ -177,6 +179,8 @@ do
         --speculative-eagle-topk 1 \
         --speculative-num-draft-tokens 4 \
         --disaggregation-transfer-backend ascend \
+        --reasoning-parser deepseek-v3 \
+        --tool-call-parser deepseekv32 \
         --trust-remote-code \
         --attention-backend ascend \
         --device npu
@@ -320,6 +324,8 @@ do
         --speculative-num-steps 1 \
         --speculative-eagle-topk 1 \
         --speculative-num-draft-tokens 2 \
+        --reasoning-parser deepseek-v3 \
+        --tool-call-parser deepseekv32 \
         --trust-remote-code \
         --attention-backend ascend \
         --device npu
@@ -372,6 +378,8 @@ do
         --speculative-eagle-topk 1 \
         --speculative-num-draft-tokens 4 \
         --disaggregation-transfer-backend ascend \
+        --reasoning-parser deepseek-v3 \
+        --tool-call-parser deepseekv32 \
         --trust-remote-code \
         --attention-backend ascend \
         --device npu
@@ -515,6 +523,8 @@ do
         --speculative-num-steps 1 \
         --speculative-eagle-topk 1 \
         --speculative-num-draft-tokens 2 \
+        --reasoning-parser deepseek-v3 \
+        --tool-call-parser deepseekv32 \
         --trust-remote-code \
         --attention-backend ascend \
         --device npu
@@ -567,6 +577,8 @@ do
         --speculative-eagle-topk 1 \
         --speculative-num-draft-tokens 4 \
         --disaggregation-transfer-backend ascend \
+        --reasoning-parser deepseek-v3 \
+        --tool-call-parser deepseekv32 \
         --trust-remote-code \
         --attention-backend ascend \
         --device npu

docs_new/docs/hardware-platforms/ascend-npus/best_practice/glm5_1.mdx

@@ -10,22 +10,22 @@ This page focuses on optimal configuration and benchmark results for GLM-5.1 on
 
 ### Low Latency
 
-| Model | Hardware | Cards | Deploy Mode | Dataset | TPOT | Quantization | Configuration |
+| Model | Hardware | Cards | Deploy Mode | Dataset | TPOT | TTFT | Quantization | Configuration |
-| --- | --- | --- | --- | --- | --- | --- | --- |
+| --- | --- | --- | --- | --- | --- | --- | --- | --- |
-| GLM-5.1 | Atlas 800I A3 | 32 | PD Disaggregation | 128K+1K | 20ms | W4A8 INT8 | [Optimal Configuration](#glm-5-1-w4a8-1p1d-32p-in128k-out1k-20ms) |
+| GLM-5.1 | Atlas 800I A3 | 32 | PD Disaggregation | 65K+1.5K (90% prefix cache hit rate) | 25ms | - | W4A8 INT8 | [Optimal Configuration](#glm-5-1-w4a8-1p1d-32p-in65k-out1k5-prefix90-25ms) |
-| GLM-5.1 | Atlas 800I A3 | 32 | PD Disaggregation | 64K+1K | 20ms | W4A8 INT8 | [Optimal Configuration](#glm-5-1-w4a8-1p1d-32p-in64k-out1k-20ms) |
-| GLM-5.1 | Atlas 800I A3 | 32 | PD Disaggregation | 65K+1.5K (90% prefix cache hit rate) | 25ms | W4A8 INT8 | [Optimal Configuration](#glm-5-1-w4a8-1p1d-32p-in65k-out1k5-prefix90-25ms) |
 
 ### High Throughput
 
-| Model | Hardware | Cards | Deploy Mode | Dataset | TPOT | Quantization | Configuration |
+| Model | Hardware | Cards | Deploy Mode | Dataset | TPOT | TTFT | Quantization | Configuration |
-| --- | --- | --- | --- | --- | --- | --- | --- |
+| --- | --- | --- | --- | --- | --- | --- | --- | --- |
-| GLM-5.1 | Atlas 800I A3 | 16 | PD Mixed | 3.5K+1.5K | 50ms | W4A8 INT8 | [Optimal Configuration](#glm-5-1-w4a8-16p-in3k5-out1k5-50ms) |
+| GLM-5.1 | Atlas 800I A3 | 16 | PD Mixed | 3.5K+1.5K | 50ms | - | W4A8 INT8 | [Optimal Configuration](#glm-5-1-w4a8-16p-in3k5-out1k5-50ms) |
-| GLM-5.1 | Atlas 800I A3 | 32 | PD Disaggregation | 16K+1K | 50ms | W4A8 INT8 | [Optimal Configuration](#glm-5-1-w4a8-1p1d-32p-in16k-out1k-50ms) |
+| GLM-5.1 | Atlas 800I A3 | 32 | PD Disaggregation | 128K+1K | 56.4ms | 13.1s | W4A8 INT8 | [Optimal Configuration](#glm-5-1-w4a8-1p1d-32p-in128k-out1k-56-4ms) |
-| GLM-5.1 | Atlas 800I A3 | 32 | PD Disaggregation | 64K+1K | 50ms | W4A8 INT8 | [Optimal Configuration](#glm-5-1-w4a8-1p1d-32p-in64k-out1k-50ms) |
+| GLM-5.1 | Atlas 800I A3 | 32 | PD Disaggregation | 16K+1K | 50ms | - | W4A8 INT8 | [Optimal Configuration](#glm-5-1-w4a8-1p1d-32p-in16k-out1k-50ms) |
-| GLM-5.1 | Atlas 800I A3 | 48 | PD Disaggregation | 65K+1.5K (100% prefix cache hit rate) | 33ms | W4A8 INT8 | [Optimal Configuration](#glm-5-1-w4a8-1p1d-48p-in65k-out1k5-prefix100-33ms) |
+| GLM-5.1 | Atlas 800I A3 | 32 | PD Disaggregation | 64K+1K | 55.2ms | 7.58s | W4A8 INT8 | [Optimal Configuration](#glm-5-1-w4a8-1p1d-32p-in64k-out1k-55-2ms) |
-| GLM-5.1 | Atlas 800I A3 | 48 | PD Disaggregation | 128K+1K (90% prefix cache hit rate) | 50ms | W4A8 INT8 | [Optimal Configuration](#glm-5-1-w4a8-2p1d-48p-in128k-out1k-prefix90-50ms) |
+| GLM-5.1 | Atlas 800I A3 | 32 | PD Disaggregation | 64K+1K | 50ms | - | W4A8 INT8 | [Optimal Configuration](#glm-5-1-w4a8-1p1d-32p-in64k-out1k-50ms) |
-| GLM-5.1 | Atlas 800I A3 | 48 | PD Disaggregation | 64K+1K (90% prefix cache hit rate) | 50ms | W4A8 INT8 | [Optimal Configuration](#glm-5-1-w4a8-4p1d-48p-in64k-out1k-prefix90-50ms) |
+| GLM-5.1 | Atlas 800I A3 | 48 | PD Disaggregation | 65K+1.5K (100% prefix cache hit rate) | 33ms | - | W4A8 INT8 | [Optimal Configuration](#glm-5-1-w4a8-1p1d-48p-in65k-out1k5-prefix100-33ms) |
+| GLM-5.1 | Atlas 800I A3 | 48 | PD Disaggregation | 128K+1K (90% prefix cache hit rate) | 50ms | - | W4A8 INT8 | [Optimal Configuration](#glm-5-1-w4a8-2p1d-48p-in128k-out1k-prefix90-50ms) |
+| GLM-5.1 | Atlas 800I A3 | 48 | PD Disaggregation | 64K+1K (90% prefix cache hit rate) | 50ms | - | W4A8 INT8 | [Optimal Configuration](#glm-5-1-w4a8-4p1d-48p-in64k-out1k-prefix90-50ms) |
 
 ## Optimal Configuration
 
@@ -122,7 +122,9 @@ do
         --speculative-algorithm NEXTN \
         --speculative-num-steps 3 \
         --speculative-eagle-topk 1 \
-        --speculative-num-draft-tokens 4
+        --speculative-num-draft-tokens 4 \
+        --reasoning-parser glm45 \
+        --tool-call-parser glm47
         break
     fi
 done
@@ -147,7 +149,7 @@ python -m sglang.bench_serving \
 
 <a id="pd-disaggregation" title="Referenced by external docs. Verify before removing."></a>
 
-### GLM-5.1 W4A8 1P1D 32P IN128K OUT1K 20ms
+### GLM-5.1 W4A8 1P1D 32P IN128K OUT1K 56.4ms
 
 **Model**: GLM-5.1
 
@@ -161,7 +163,9 @@ python -m sglang.bench_serving \
 
 **Dataset**: 128K+1K
 
-**TPOT**: 20ms
+**TPOT**: 56.4ms
+
+**TTFT**: 13.1s
 
 #### Model Deployment
 
@@ -241,7 +245,7 @@ do
         --disaggregation-transfer-backend ascend \
         --max-running-requests 16 \
         --served-model-name glm-5 \
-        --chunked-prefill-size 16384 \
+        --chunked-prefill-size 8192 \
         --max-prefill-tokens 180000 \
         --moe-a2a-backend deepep \
         --deepep-mode normal \
@@ -255,6 +259,8 @@ do
         --enable-dp-lm-head \
         --moe-dense-tp 1 \
         --pp-size 8 \
+        --reasoning-parser glm45 \
+        --tool-call-parser glm47 \
         --trust-remote-code
         NODE_RANK=$i
         break
@@ -306,6 +312,8 @@ do
         --dtype bfloat16 \
         --load-balance-method round_robin \
         --speculative-draft-model-quantization unquant \
+        --reasoning-parser glm45 \
+        --tool-call-parser glm47 \
         --trust-remote-code
         NODE_RANK=$i
         break
@@ -452,6 +460,8 @@ do
         --attn-cp-size 8 \
         --enable-dp-lm-head \
         --moe-dense-tp 1 \
+        --reasoning-parser glm45 \
+        --tool-call-parser glm47 \
         --trust-remote-code
         NODE_RANK=$i
         break
@@ -507,6 +517,8 @@ do
         --speculative-num-steps 3 \
         --speculative-eagle-topk 1 \
         --speculative-num-draft-tokens 4 \
+        --reasoning-parser glm45 \
+        --tool-call-parser glm47 \
         --trust-remote-code
         NODE_RANK=$i
         break
@@ -547,7 +559,7 @@ python -m sglang.bench_serving \
     --random-range-ratio 1
 ```
 
-### GLM-5.1 W4A8 1P1D 32P IN64K OUT1K 20ms
+### GLM-5.1 W4A8 1P1D 32P IN64K OUT1K 55.2ms
 
 **Model**: GLM-5.1
 
@@ -561,7 +573,9 @@ python -m sglang.bench_serving \
 
 **Dataset**: 64K+1K
 
-**TPOT**: 20ms
+**TPOT**: 55.2ms
+
+**TTFT**: 7.58s
 
 #### Model Deployment
 
@@ -641,7 +655,7 @@ do
         --disaggregation-transfer-backend ascend \
         --max-running-requests 16 \
         --served-model-name glm-5 \
-        --chunked-prefill-size 16384 \
+        --chunked-prefill-size 8192 \
         --max-prefill-tokens 180000 \
         --moe-a2a-backend deepep \
         --deepep-mode normal \
@@ -655,6 +669,8 @@ do
         --enable-dp-lm-head \
         --moe-dense-tp 1 \
         --pp-size 8 \
+        --reasoning-parser glm45 \
+        --tool-call-parser glm47 \
         --trust-remote-code
         NODE_RANK=$i
         break
@@ -706,6 +722,8 @@ do
         --dtype bfloat16 \
         --load-balance-method round_robin \
         --speculative-draft-model-quantization unquant \
+        --reasoning-parser glm45 \
+        --tool-call-parser glm47 \
         --trust-remote-code
         NODE_RANK=$i
         break
@@ -854,6 +872,8 @@ do
         --enable-dp-lm-head \
         --moe-dense-tp 1 \
         --pp-size 8 \
+        --reasoning-parser glm45 \
+        --tool-call-parser glm47 \
         --trust-remote-code
         NODE_RANK=$i
         break
@@ -905,6 +925,8 @@ do
         --dtype bfloat16 \
         --load-balance-method round_robin \
         --speculative-draft-model-quantization unquant \
+        --reasoning-parser glm45 \
+        --tool-call-parser glm47 \
         --trust-remote-code
         NODE_RANK=$i
         break
@@ -1051,6 +1073,8 @@ do
         --attn-cp-size 8 \
         --enable-dp-lm-head \
         --moe-dense-tp 1 \
+        --reasoning-parser glm45 \
+        --tool-call-parser glm47 \
         --trust-remote-code
         NODE_RANK=$i
         break
@@ -1106,6 +1130,8 @@ do
         --speculative-num-steps 3 \
         --speculative-eagle-topk 1 \
         --speculative-num-draft-tokens 4 \
+        --reasoning-parser glm45 \
+        --tool-call-parser glm47 \
         --trust-remote-code
         NODE_RANK=$i
         break
@@ -1248,6 +1274,8 @@ do
         --disable-shared-experts-fusion \
         --disable-cuda-graph \
         --dtype bfloat16 \
+        --reasoning-parser glm45 \
+        --tool-call-parser glm47 \
         --trust-remote-code
         NODE_RANK=$i
         break
@@ -1289,7 +1317,6 @@ do
         --quantization modelslim \
         --served-model-name glm-5 \
         --moe-a2a-backend deepep \
-        --enable-dp-attention \
         --deepep-mode low_latency \
         --enable-dp-lm-head \
         --moe-dense-tp 1 \
@@ -1307,6 +1334,8 @@ do
         --disable-shared-experts-fusion \
         --dtype bfloat16 \
         --load-balance-method round_robin \
+        --reasoning-parser glm45 \
+        --tool-call-parser glm47 \
         --trust-remote-code
         NODE_RANK=$i
         break
@@ -1455,6 +1484,8 @@ do
         --enable-dp-lm-head \
         --moe-dense-tp 1 \
         --pp-size 8 \
+        --reasoning-parser glm45 \
+        --tool-call-parser glm47 \
         --trust-remote-code
         NODE_RANK=$i
         break
@@ -1510,6 +1541,8 @@ do
         --speculative-num-steps 3 \
         --speculative-eagle-topk 1 \
         --speculative-num-draft-tokens 4 \
+        --reasoning-parser glm45 \
+        --tool-call-parser glm47 \
         --trust-remote-code
         NODE_RANK=$i
         break
@@ -1664,6 +1697,8 @@ do
         --enable-dp-lm-head \
         --moe-dense-tp 1 \
         --pp-size 4 \
+        --reasoning-parser glm45 \
+        --tool-call-parser glm47 \
         --trust-remote-code
         NODE_RANK=$i
         break
@@ -1719,6 +1754,8 @@ do
         --speculative-num-steps 3 \
         --speculative-eagle-topk 1 \
         --speculative-num-draft-tokens 4 \
+        --reasoning-parser glm45 \
+        --tool-call-parser glm47 \
         --trust-remote-code
         NODE_RANK=$i
         break

docs_new/docs/hardware-platforms/ascend-npus/best_practice/kimi_k2_6.mdx

@@ -10,22 +10,22 @@ This page focuses on optimal configuration and benchmark results for Kimi-K2.6 o
 
 ### Low Latency
 
-| Model | Hardware | Cards | Deploy Mode | Dataset | TPOT | Quantization | Configuration |
+| Model | Hardware | Cards | Deploy Mode | Dataset | TPOT | TTFT | Quantization | Configuration |
-| --- | --- | --- | --- | --- | --- | --- | --- |
+| --- | --- | --- | --- | --- | --- | --- | --- | --- |
-| Kimi-K2.6 | Atlas 800I A3 | 8 | PD Mixed | 3.5K+1.5K | 20ms | W4A8 INT8 | [Optimal Configuration](#kimi-k2-6-w4a8-8p-in3k5-out1k5-20ms) |
+| Kimi-K2.6 | Atlas 800I A3 | 8 | PD Mixed | 3.5K+1.5K | 20ms | - | W4A8 INT8 | [Optimal Configuration](#kimi-k2-6-w4a8-8p-in3k5-out1k5-20ms) |
 
 ### High Throughput
 
-| Model | Hardware | Cards | Deploy Mode | Dataset | TPOT | Quantization | Configuration |
+| Model | Hardware | Cards | Deploy Mode | Dataset | TPOT | TTFT | Quantization | Configuration |
-| --- | --- | --- | --- | --- | --- | --- | --- |
+| --- | --- | --- | --- | --- | --- | --- | --- | --- |
-| Kimi-K2.6 | Atlas 800I A3 | 16 | PD Mixed | 64K+1K | 100ms | W4A8 INT8 | [Optimal Configuration](#kimi-k2-6-w4a8-16p-in64k-out1k-100ms) |
+| Kimi-K2.6 | Atlas 800I A3 | 16 | PD Mixed | 64K+1K | 100ms | - | W4A8 INT8 | [Optimal Configuration](#kimi-k2-6-w4a8-16p-in64k-out1k-100ms) |
-| Kimi-K2.6 | Atlas 800I A3 | 16 | PD Disaggregation | 128K+1K | 100ms | W4A8 INT8 | [Optimal Configuration](#kimi-k2-6-w4a8-1p1d-16p-in128k-out1k-100ms) |
+| Kimi-K2.6 | Atlas 800I A3 | 16 | PD Disaggregation | 128K+1K | 100ms | - | W4A8 INT8 | [Optimal Configuration](#kimi-k2-6-w4a8-1p1d-16p-in128k-out1k-100ms) |
-| Kimi-K2.6 | Atlas 800I A3 | 16 | PD Disaggregation | 128K+1K (90% prefix cache hit rate) | 100ms | W4A8 INT8 | [Optimal Configuration](#kimi-k2-6-w4a8-1p1d-16p-in128k-out1k-prefix90-100ms) |
+| Kimi-K2.6 | Atlas 800I A3 | 16 | PD Disaggregation | 128K+1K (90% prefix cache hit rate) | 100ms | 5s | W4A8 INT8 | [Optimal Configuration](#kimi-k2-6-w4a8-1p1d-16p-in128k-out1k-prefix90-100ms) |
-| Kimi-K2.6 | Atlas 800I A3 | 16 | PD Disaggregation | 64K+1.5K | 100ms | W4A8 INT8 | [Optimal Configuration](#kimi-k2-6-w4a8-1p1d-16p-in64k-out1k5-100ms) |
+| Kimi-K2.6 | Atlas 800I A3 | 16 | PD Disaggregation | 64K+1.5K | 100ms | - | W4A8 INT8 | [Optimal Configuration](#kimi-k2-6-w4a8-1p1d-16p-in64k-out1k5-100ms) |
-| Kimi-K2.6 | Atlas 800I A3 | 16 | PD Disaggregation | 64K+1.5K (90% prefix cache hit rate) | 100ms | W4A8 INT8 | [Optimal Configuration](#kimi-k2-6-w4a8-1p1d-16p-in64k-out1k5-prefix90-100ms) |
+| Kimi-K2.6 | Atlas 800I A3 | 16 | PD Disaggregation | 64K+1.5K (90% prefix cache hit rate) | 100ms | 3s | W4A8 INT8 | [Optimal Configuration](#kimi-k2-6-w4a8-1p1d-16p-in64k-out1k5-prefix90-100ms) |
-| Kimi-K2.6 | Atlas 800I A3 | 8 | PD Mixed | 1024x1024 (30)+1024 | 50ms | W4A8 INT8 | [Optimal Configuration](#kimi-k2-6-w4a8-8p-in1024x1024-30-out1024-50ms) |
+| Kimi-K2.6 | Atlas 800I A3 | 8 | PD Mixed | 1024x1024 (30)+1024 | 50ms | - | W4A8 INT8 | [Optimal Configuration](#kimi-k2-6-w4a8-8p-in1024x1024-30-out1024-50ms) |
-| Kimi-K2.6 | Atlas 800I A3 | 8 | PD Mixed | 1080p_30+256 | 50ms | W4A8 INT8 | [Optimal Configuration](#kimi-k2-6-w4a8-8p-in1080p-30-out256-50ms) |
+| Kimi-K2.6 | Atlas 800I A3 | 8 | PD Mixed | 1080p_30+256 | 50ms | - | W4A8 INT8 | [Optimal Configuration](#kimi-k2-6-w4a8-8p-in1080p-30-out256-50ms) |
-| Kimi-K2.6 | Atlas 800I A3 | 8 | PD Mixed | 3.5K+1.5K | 50ms | W4A8 INT8 | [Optimal Configuration](#kimi-k2-6-w4a8-8p-in3k5-out1k5-50ms) |
+| Kimi-K2.6 | Atlas 800I A3 | 8 | PD Mixed | 3.5K+1.5K | 50ms | - | W4A8 INT8 | [Optimal Configuration](#kimi-k2-6-w4a8-8p-in3k5-out1k5-50ms) |
 
 ## Optimal Configuration
 
@@ -111,7 +111,7 @@ do
         --quantization modelslim \
         --dtype bfloat16 \
         --tp-size 32 \
-        --mem-fraction-static 0.55 \
+        --mem-fraction-static 0.662 \
         --max-running-requests 32 \
         --chunked-prefill-size 262144 \
         --context-length 75000 \
@@ -129,7 +129,9 @@ do
         --speculative-num-steps 3 \
         --speculative-eagle-topk 1 \
         --speculative-num-draft-tokens 4 \
-        --speculative-draft-model-quantization unquant
+        --speculative-draft-model-quantization unquant \
+        --reasoning-parser kimi_k2 \
+        --tool-call-parser kimi_k2
         break
     fi
 done
@@ -248,14 +250,13 @@ do
         --device npu \
         --tp-size 16 \
         --disable-radix-cache \
-        --disable-cuda-graph \
         --mem-fraction-static 0.78 \
-        --max-running-requests 1 \
+        --max-running-requests 2 \
         --moe-a2a-backend deepep \
         --deepep-mode auto \
         --chunked-prefill-size 16384 \
-        --prefill-max-requests 1 \
+        --prefill-max-requests 2 \
-        --max-prefill-tokens 131072 \
+        --max-prefill-tokens 65536 \
         --enable-multimodal \
         --mm-attention-backend ascend_attn \
         --sampling-backend ascend
@@ -292,8 +293,8 @@ do
         --attention-backend ascend \
         --device npu \
         --tp-size 16 \
-        --mem-fraction-static 0.73 \
+        --mem-fraction-static 0.82 \
-        --max-running-requests 1 \
+        --max-running-requests 2 \
         --enable-dp-attention \
         --dp-size 1 \
         --enable-dp-lm-head \
@@ -309,7 +310,9 @@ do
         --speculative-num-steps 3 \
         --speculative-eagle-topk 1 \
         --speculative-num-draft-tokens 4 \
-        --speculative-draft-model-quantization unquant
+        --speculative-draft-model-quantization unquant \
+        --reasoning-parser kimi_k2 \
+        --tool-call-parser kimi_k2
         NODE_RANK=$i
         break
     fi
@@ -366,6 +369,8 @@ python -m sglang.bench_serving \
 
 **TPOT**: 100ms
 
+**TTFT**: 5s
+
 #### Model Deployment
 
 ```bash Command
@@ -452,7 +457,9 @@ do
         --max-prefill-tokens 65536 \
         --enable-multimodal \
         --mm-attention-backend ascend_attn \
-        --sampling-backend ascend
+        --sampling-backend ascend \
+        --reasoning-parser kimi_k2 \
+        --tool-call-parser kimi_k2
         NODE_RANK=$i
         break
     fi
@@ -486,7 +493,7 @@ do
         --attention-backend ascend \
         --device npu \
         --tp-size 16 \
-        --mem-fraction-static 0.73 \
+        --mem-fraction-static 0.82 \
         --max-running-requests 2 \
         --enable-dp-attention \
         --dp-size 1 \
@@ -503,7 +510,9 @@ do
         --speculative-num-steps 3 \
         --speculative-eagle-topk 1 \
         --speculative-num-draft-tokens 4 \
-        --speculative-draft-model-quantization unquant
+        --speculative-draft-model-quantization unquant \
+        --reasoning-parser kimi_k2 \
+        --tool-call-parser kimi_k2
         NODE_RANK=$i
         break
     fi
@@ -619,13 +628,8 @@ do
     then
         echo "${P_IP[$i]}"
         export GLOO_SOCKET_IFNAME=<network-interface>
-        export HCCL_BUFFSIZE=8
+        export HCCL_BUFFSIZE=1800
         export HCCL_SOCKET_IFNAME=<network-interface>
-        export SGLANG_ENABLE_TP_MEMORY_INBALANCE_CHECK=0
-        export SGLANG_ZBAL_BOOTSTRAP_URL=tcp://127.0.0.1:24699
-        export SGLANG_ZBAL_LOCAL_MEM_SIZE=61184
-        export ZBAL_ENABLE_GRAPH=1
-        export ZBAL_NPU_ALLOC_CONF=use_vmm_for_static_memory:True
 
         python3 -m sglang.launch_server \
         --model-path ${MODEL_PATH} \
@@ -653,7 +657,9 @@ do
         --max-prefill-tokens 65536 \
         --enable-multimodal \
         --mm-attention-backend ascend_attn \
-        --sampling-backend ascend
+        --sampling-backend ascend \
+        --reasoning-parser kimi_k2 \
+        --tool-call-parser kimi_k2
         NODE_RANK=$i
         break
     fi
@@ -688,7 +694,7 @@ do
         --device npu \
         --tp-size 16 \
         --mem-fraction-static 0.82 \
-        --max-running-requests 1 \
+        --max-running-requests 16 \
         --enable-dp-attention \
         --dp-size 1 \
         --enable-dp-lm-head \
@@ -699,6 +705,8 @@ do
         --moe-a2a-backend deepep \
         --deepep-mode auto \
         --cuda-graph-bs 16 \
+        --reasoning-parser kimi_k2 \
+        --tool-call-parser kimi_k2 \
         --speculative-algorithm EAGLE3 \
         --speculative-draft-model-path $DRAFT_MODEL_PATH \
         --speculative-num-steps 4 \
@@ -761,6 +769,8 @@ python -m sglang.bench_serving \
 
 **TPOT**: 100ms
 
+**TTFT**: 3s
+
 #### Model Deployment
 
 ```bash Command
@@ -815,13 +825,8 @@ do
     then
         echo "${P_IP[$i]}"
         export GLOO_SOCKET_IFNAME=<network-interface>
-        export HCCL_BUFFSIZE=8
+        export HCCL_BUFFSIZE=1800
         export HCCL_SOCKET_IFNAME=<network-interface>
-        export SGLANG_ENABLE_TP_MEMORY_INBALANCE_CHECK=0
-        export SGLANG_ZBAL_BOOTSTRAP_URL=tcp://127.0.0.1:24699
-        export SGLANG_ZBAL_LOCAL_MEM_SIZE=61184
-        export ZBAL_ENABLE_GRAPH=1
-        export ZBAL_NPU_ALLOC_CONF=use_vmm_for_static_memory:True
 
         python3 -m sglang.launch_server \
         --model-path ${MODEL_PATH} \
@@ -847,7 +852,9 @@ do
         --max-prefill-tokens 65536 \
         --enable-multimodal \
         --mm-attention-backend ascend_attn \
-        --sampling-backend ascend
+        --sampling-backend ascend \
+        --reasoning-parser kimi_k2 \
+        --tool-call-parser kimi_k2
         NODE_RANK=$i
         break
     fi
@@ -893,6 +900,8 @@ do
         --moe-a2a-backend deepep \
         --deepep-mode auto \
         --cuda-graph-bs 1 2 4 6 8 \
+        --reasoning-parser kimi_k2 \
+        --tool-call-parser kimi_k2 \
         --speculative-algorithm EAGLE3 \
         --speculative-draft-model-path $DRAFT_MODEL_PATH \
         --speculative-num-steps 4 \
@@ -1013,7 +1022,7 @@ python3 -m sglang.launch_server \
     --device npu \
     --attention-backend ascend \
     --tp-size 16 \
-    --mem-fraction-static 0.76 \
+    --mem-fraction-static 0.872 \
     --max-running-requests 176 \
     --chunked-prefill-size 32768 \
     --context-length 8192 \
@@ -1025,7 +1034,7 @@ python3 -m sglang.launch_server \
     --dp-size 16 \
     --moe-a2a-backend deepep \
     --deepep-mode auto \
-    --cuda-graph-bs 1 2 4 8 9 10 11 \
+    --cuda-graph-bs-decode 1 2 4 8 9 10 11 \
     --disable-radix-cache \
     --speculative-algorithm EAGLE3 \
     --speculative-draft-model-path $DRAFT_MODEL_PATH \
@@ -1034,7 +1043,9 @@ python3 -m sglang.launch_server \
     --speculative-num-draft-tokens 3 \
     --speculative-draft-model-quantization unquant \
     --prefill-delayer-max-delay-passes 200 \
-    --enable-prefill-delayer
+    --enable-prefill-delayer \
+    --reasoning-parser kimi_k2 \
+    --tool-call-parser kimi_k2
 ```
 
 #### Benchmark
@@ -1124,7 +1135,7 @@ python3 -m sglang.launch_server \
     --attention-backend ascend \
     --tp-size 16 \
     --base-gpu-id 0 \
-    --mem-fraction-static 0.74 \
+    --mem-fraction-static 0.852 \
     --max-running-requests 64 \
     --chunked-prefill-size 16384 \
     --context-length 8192 \
@@ -1145,7 +1156,9 @@ python3 -m sglang.launch_server \
     --speculative-num-draft-tokens 3 \
     --speculative-draft-model-quantization unquant \
     --prefill-delayer-max-delay-passes 200 \
-    --enable-prefill-delayer
+    --enable-prefill-delayer \
+    --reasoning-parser kimi_k2 \
+    --tool-call-parser kimi_k2
 ```
 
 #### Benchmark
@@ -1237,7 +1250,7 @@ python3 -m sglang.launch_server \
     --quantization modelslim \
     --dtype bfloat16 \
     --tp-size 16 \
-    --mem-fraction-static 0.753 \
+    --mem-fraction-static 0.865 \
     --max-running-requests 80 \
     --chunked-prefill-size 32768 \
     --context-length 6144 \
@@ -1249,7 +1262,7 @@ python3 -m sglang.launch_server \
     --dp-size 16 \
     --moe-a2a-backend deepep \
     --deepep-mode auto \
-    --cuda-graph-bs 1 2 3 4 5 \
+    --cuda-graph-bs-decode 1 2 3 4 5 \
     --disable-radix-cache \
     --model-loader-extra-config '{"enable_multithread_load": true}' \
     --speculative-algorithm EAGLE3 \
@@ -1259,7 +1272,9 @@ python3 -m sglang.launch_server \
     --speculative-num-draft-tokens 5 \
     --speculative-draft-model-quantization unquant \
     --prefill-delayer-max-delay-passes 200 \
-    --enable-prefill-delayer
+    --enable-prefill-delayer \
+    --reasoning-parser kimi_k2 \
+    --tool-call-parser kimi_k2
 ```
 
 #### Benchmark
@@ -1346,7 +1361,7 @@ python3 -m sglang.launch_server \
     --quantization modelslim \
     --dtype bfloat16 \
     --tp-size 16 \
-    --mem-fraction-static 0.783 \
+    --mem-fraction-static 0.895 \
     --max-running-requests 208 \
     --chunked-prefill-size 32768 \
     --context-length 6144 \
@@ -1358,7 +1373,7 @@ python3 -m sglang.launch_server \
     --dp-size 16 \
     --moe-a2a-backend deepep \
     --deepep-mode auto \
-    --cuda-graph-bs 1 2 4 8 12 13 \
+    --cuda-graph-bs-decode 1 2 4 8 12 13 \
     --disable-radix-cache \
     --model-loader-extra-config '{"enable_multithread_load": true}' \
     --speculative-algorithm EAGLE3 \
@@ -1368,7 +1383,9 @@ python3 -m sglang.launch_server \
     --speculative-num-draft-tokens 5 \
     --speculative-draft-model-quantization unquant \
     --prefill-delayer-max-delay-passes 200 \
-    --enable-prefill-delayer
+    --enable-prefill-delayer \
+    --reasoning-parser kimi_k2 \
+    --tool-call-parser kimi_k2
 ```
 
 #### Benchmark

docs_new/docs/hardware-platforms/ascend-npus/best_practice/mimo_v2_flash.mdx

@@ -0,0 +1,769 @@
+---
+title: "MiMo-V2-Flash"
+metatags:
+  description: "Best Practice for MiMo-V2-Flash on Ascend NPU"
+---
+
+This guide describes the best practice data for MiMo-V2-Flash on the Ascend NPU.
+
+### Low Latency
+
+| Model | Hardware | Cards | Deploy Mode | Dataset | TPOT | TTFT | Quantization | Configuration |
+| --- | --- | --- | --- | --- | --- | --- | --- | --- |
+| MiMo-V2-Flash | Atlas 800I A3 | 12 | PD Disaggregation | 16K+1K | 20ms | - | W8A8 INT8 | [Optimal Configuration](#mimo-v2-flash-1p1d-12p-in16k-out1k-tpot-20ms) |
+| MiMo-V2-Flash | Atlas 800I A3 | 12 | PD Disaggregation | 32K+1K | 20ms | - | W8A8 INT8 | [Optimal Configuration](#mimo-v2-flash-1p1d-12p-in32k-out1k-tpot-20ms) |
+
+### High Throughput
+
+| Model | Hardware | Cards | Deploy Mode | Dataset | TPOT | TTFT | Quantization | Configuration |
+| --- | --- | --- | --- | --- | --- | --- | --- | --- |
+| MiMo-V2-Flash | Atlas 800I A3 | 12 | PD Disaggregation | 16K+1 | - | 5s | W8A8 INT8 | [Optimal Configuration](#mimo-v2-flash-1p1d-12p-in16k-out1-ttft-5s) |
+| MiMo-V2-Flash | Atlas 800I A3 | 12 | PD Disaggregation | 32K+1 | - | 5s | W8A8 INT8 | [Optimal Configuration](#mimo-v2-flash-1p1d-12p-in32k-out1-ttft-5s) |
+
+## Optimal Configuration
+
+<a id="pd-disaggregation" title="Referenced by external docs. Verify before removing."></a>
+
+### MiMo-V2-Flash 1P1D 12P IN16K OUT1 TTFT 5s
+
+**Model**: MiMo-V2-Flash
+
+**Hardware**: Atlas 800I A3
+
+**Cards**: 12
+
+**Deploy Mode**: PD Disaggregation
+
+**Quantization**: W8A8 INT8
+
+**Dataset**: 16K+1
+
+**TTFT**: 5s
+
+#### Model Deployment
+
+```bash Command
+# ============================================================
+# Before running, update the following variables:
+#   P_IP: prefill node IP address
+#   D_IP: decode node IP address
+#   ASCEND_MF_STORE_URL: prefill node IP with port
+#   MODEL_PATH: path to the model weights directory
+#   HCCL_SOCKET_IFNAME: network interface name for HCCL
+#   GLOO_SOCKET_IFNAME: network interface name for Gloo
+# ============================================================
+
+
+echo performance | tee /sys/devices/system/cpu/cpu*/cpufreq/scaling_governor
+sysctl -w vm.swappiness=0
+sysctl -w kernel.numa_balancing=0
+sysctl -w kernel.sched_migration_cost_ns=50000
+
+unset https_proxy
+unset http_proxy
+unset HTTPS_PROXY
+unset HTTP_PROXY
+unset ASCEND_LAUNCH_BLOCKING
+
+source /usr/local/Ascend/ascend-toolkit/set_env.sh
+source /usr/local/Ascend/nnal/atb/set_env.sh
+
+export ASCEND_USE_FIA=1
+export DEEPEP_NORMAL_LONG_SEQ_PER_ROUND_TOKENS=3584
+export DEEPEP_NORMAL_LONG_SEQ_ROUND=32
+export DEEP_NORMAL_MODE_USE_INT8_QUANT=1
+export HCCL_CONNECT_TIMEOUT=1800
+export HCCL_OP_EXPANSION_MODE=AIV
+export PYTORCH_NPU_ALLOC_CONF=expandable_segments:True
+export SGLANG_DEEPEP_BF16_DISPATCH=0
+export SGLANG_DISAGGREGATION_BOOTSTRAP_TIMEOUT=3600
+export SGLANG_DISAGGREGATION_WAITING_TIMEOUT=3600
+export SGLANG_ENABLE_OVERLAP_PLAN_STREAM=0
+export SGLANG_ENABLE_SPEC_V2=1
+export SGLANG_SET_CPU_AFFINITY=1
+export STREAMS_PER_DEVICE=32
+
+P_IP=('<your prefill ip>')
+D_IP=('<your decode ip>')
+
+export ASCEND_MF_STORE_URL="tcp://<your prefill ip>:24670"
+
+MODEL_PATH=/path/to/model-weights
+
+LOCAL_HOST1=`hostname -I|awk -F " " '{print$1}'`
+LOCAL_HOST2=`hostname -I|awk -F " " '{print$2}'`
+echo "${LOCAL_HOST1}"
+echo "${LOCAL_HOST2}"
+# prefill
+for i in "${!P_IP[@]}";
+do
+    if [[ "$LOCAL_HOST1" == "${P_IP[$i]}" || "$LOCAL_HOST2" == "${P_IP[$i]}" ]];
+    then
+        echo "${P_IP[$i]}"
+        export GLOO_SOCKET_IFNAME=<network-interface>
+        export HCCL_BUFFSIZE=1024
+        export HCCL_SOCKET_IFNAME=<network-interface>
+        export SGLANG_DEEPEP_NUM_MAX_DISPATCH_TOKENS_PER_RANK=32
+        export SGLANG_DISAGGREGATION_FORCE_QUERY_PREFILL_DP_RANK=1
+
+        python3 -m sglang.launch_server \
+        --model-path ${MODEL_PATH} \
+        --disaggregation-mode prefill \
+        --host ${P_IP[$i]} \
+        --port 8000 \
+        --disaggregation-bootstrap-port 8998 \
+        --node-rank 0 \
+        --attention-backend ascend \
+        --device npu \
+        --tp-size 8 \
+        --nnodes 1 \
+        --chunked-prefill-size 8192 \
+        --trust-remote-code \
+        --max-running-requests 64 \
+        --mem-fraction-static 0.8 \
+        --swa-full-tokens-ratio 0.3 \
+        --disaggregation-transfer-backend ascend \
+        --disable-radix-cache \
+        --disable-cuda-graph \
+        --disable-piecewise-cuda-graph \
+        --dp-size 2
+        NODE_RANK=$i
+        break
+    fi
+done
+
+# decode
+for i in "${!D_IP[@]}";
+do
+    if [[ "$LOCAL_HOST1" == "${D_IP[$i]}" || "$LOCAL_HOST2" == "${D_IP[$i]}" ]];
+    then
+        echo "${D_IP[$i]}"
+        export GLOO_SOCKET_IFNAME=<network-interface>
+        export HCCL_BUFFSIZE=800
+        export HCCL_SOCKET_IFNAME=<network-interface>
+        export SGLANG_DEEPEP_NUM_MAX_DISPATCH_TOKENS_PER_RANK=128
+
+        python3 -m sglang.launch_server \
+        --model-path ${MODEL_PATH} \
+        --disaggregation-mode decode \
+        --host ${D_IP[$i]} \
+        --port 8001 \
+        --attention-backend ascend \
+        --device npu \
+        --tp-size 16 \
+        --nnodes 1 \
+        --trust-remote-code \
+        --max-running-requests 64 \
+        --mem-fraction-static 0.8 \
+        --swa-full-tokens-ratio 0.3 \
+        --cuda-graph-bs 1 2 4 8 12 16 20 24 28 32 \
+        --disaggregation-transfer-backend ascend \
+        --speculative-algorithm EAGLE \
+        --speculative-num-steps 3 \
+        --speculative-eagle-topk 1 \
+        --speculative-num-draft-tokens 4 \
+        --enable-multi-layer-eagle \
+        --disable-radix-cache \
+        --dp-size 2 \
+        --enable-dp-attention \
+        --enable-dp-lm-head \
+        --moe-a2a-backend deepep \
+        --deepep-mode low_latency
+        NODE_RANK=$i
+        break
+    fi
+done
+```
+
+```shell Command
+# ============================================================
+# Before running, replace the following placeholders:
+#   <your prefill ip>: prefill node IP address
+#   <your decode ip>: decode node IP address
+# ============================================================
+
+python -m sglang_router.launch_router \
+    --pd-disaggregation \
+    --policy cache_aware \
+    --prefill http://<your prefill ip>:8000 8998 \
+    --decode http://<your decode ip>:8001 \
+    --host 127.0.0.1 \
+    --port 6688 \
+    --health-check-interval-secs 3600 --mini-lb
+```
+
+#### Benchmark
+
+We tested it based on the `RANDOM` dataset.
+
+```shell Command
+python -m sglang.bench_serving \
+    --dataset-name random \
+    --backend sglang \
+    --host 127.0.0.1 \
+    --port 6688 \
+    --max-concurrency 64 \
+    --random-input-len 16000 \
+    --random-output-len 1 \
+    --num-prompts 128 \
+    --random-range-ratio 1 \
+    --request-rate 0.4
+```
+
+### MiMo-V2-Flash 1P1D 12P IN16K OUT1K TPOT 20ms
+
+**Model**: MiMo-V2-Flash
+
+**Hardware**: Atlas 800I A3
+
+**Cards**: 12
+
+**Deploy Mode**: PD Disaggregation
+
+**Quantization**: W8A8 INT8
+
+**Dataset**: 16K+1K
+
+**TPOT**: 20ms
+
+#### Model Deployment
+
+```bash Command
+# ============================================================
+# Before running, update the following variables:
+#   P_IP: prefill node IP address
+#   D_IP: decode node IP address
+#   ASCEND_MF_STORE_URL: prefill node IP with port
+#   MODEL_PATH: path to the model weights directory
+#   HCCL_SOCKET_IFNAME: network interface name for HCCL
+#   GLOO_SOCKET_IFNAME: network interface name for Gloo
+# ============================================================
+
+
+echo performance | tee /sys/devices/system/cpu/cpu*/cpufreq/scaling_governor
+sysctl -w vm.swappiness=0
+sysctl -w kernel.numa_balancing=0
+sysctl -w kernel.sched_migration_cost_ns=50000
+
+unset https_proxy
+unset http_proxy
+unset HTTPS_PROXY
+unset HTTP_PROXY
+unset ASCEND_LAUNCH_BLOCKING
+
+source /usr/local/Ascend/ascend-toolkit/set_env.sh
+source /usr/local/Ascend/nnal/atb/set_env.sh
+
+export ASCEND_USE_FIA=1
+export DEEPEP_NORMAL_LONG_SEQ_PER_ROUND_TOKENS=3584
+export DEEPEP_NORMAL_LONG_SEQ_ROUND=32
+export DEEP_NORMAL_MODE_USE_INT8_QUANT=1
+export HCCL_CONNECT_TIMEOUT=1800
+export HCCL_OP_EXPANSION_MODE=AIV
+export PYTORCH_NPU_ALLOC_CONF=expandable_segments:True
+export SGLANG_DEEPEP_BF16_DISPATCH=0
+export SGLANG_DISAGGREGATION_BOOTSTRAP_TIMEOUT=3600
+export SGLANG_DISAGGREGATION_WAITING_TIMEOUT=3600
+export SGLANG_ENABLE_OVERLAP_PLAN_STREAM=0
+export SGLANG_ENABLE_SPEC_V2=1
+export SGLANG_SET_CPU_AFFINITY=1
+export STREAMS_PER_DEVICE=32
+
+P_IP=('<your prefill ip>')
+D_IP=('<your decode ip>')
+
+export ASCEND_MF_STORE_URL="tcp://<your prefill ip>:24670"
+
+MODEL_PATH=/path/to/model-weights
+
+LOCAL_HOST1=`hostname -I|awk -F " " '{print$1}'`
+LOCAL_HOST2=`hostname -I|awk -F " " '{print$2}'`
+echo "${LOCAL_HOST1}"
+echo "${LOCAL_HOST2}"
+# prefill
+for i in "${!P_IP[@]}";
+do
+    if [[ "$LOCAL_HOST1" == "${P_IP[$i]}" || "$LOCAL_HOST2" == "${P_IP[$i]}" ]];
+    then
+        echo "${P_IP[$i]}"
+        export GLOO_SOCKET_IFNAME=<network-interface>
+        export HCCL_BUFFSIZE=1024
+        export HCCL_SOCKET_IFNAME=<network-interface>
+        export SGLANG_DEEPEP_NUM_MAX_DISPATCH_TOKENS_PER_RANK=32
+        export SGLANG_DISAGGREGATION_FORCE_QUERY_PREFILL_DP_RANK=1
+
+        python3 -m sglang.launch_server \
+        --model-path ${MODEL_PATH} \
+        --disaggregation-mode prefill \
+        --host ${P_IP[$i]} \
+        --port 8000 \
+        --disaggregation-bootstrap-port 8998 \
+        --node-rank 0 \
+        --attention-backend ascend \
+        --device npu \
+        --tp-size 8 \
+        --nnodes 1 \
+        --chunked-prefill-size 8192 \
+        --trust-remote-code \
+        --max-running-requests 64 \
+        --mem-fraction-static 0.8 \
+        --swa-full-tokens-ratio 0.3 \
+        --disaggregation-transfer-backend ascend \
+        --disable-radix-cache \
+        --disable-cuda-graph \
+        --disable-piecewise-cuda-graph \
+        --dp-size 2
+        NODE_RANK=$i
+        break
+    fi
+done
+
+# decode
+for i in "${!D_IP[@]}";
+do
+    if [[ "$LOCAL_HOST1" == "${D_IP[$i]}" || "$LOCAL_HOST2" == "${D_IP[$i]}" ]];
+    then
+        echo "${D_IP[$i]}"
+        export GLOO_SOCKET_IFNAME=<network-interface>
+        export HCCL_BUFFSIZE=800
+        export HCCL_SOCKET_IFNAME=<network-interface>
+        export SGLANG_DEEPEP_NUM_MAX_DISPATCH_TOKENS_PER_RANK=128
+
+        python3 -m sglang.launch_server \
+        --model-path ${MODEL_PATH} \
+        --disaggregation-mode decode \
+        --host ${D_IP[$i]} \
+        --port 8001 \
+        --attention-backend ascend \
+        --device npu \
+        --tp-size 16 \
+        --nnodes 1 \
+        --trust-remote-code \
+        --max-running-requests 32 \
+        --mem-fraction-static 0.8 \
+        --swa-full-tokens-ratio 0.3 \
+        --cuda-graph-bs 1 2 4 8 12 16 \
+        --disaggregation-transfer-backend ascend \
+        --speculative-algorithm EAGLE \
+        --speculative-num-steps 3 \
+        --speculative-eagle-topk 1 \
+        --speculative-num-draft-tokens 4 \
+        --enable-multi-layer-eagle \
+        --disable-radix-cache \
+        --dp-size 2 \
+        --enable-dp-attention \
+        --enable-dp-lm-head \
+        --moe-a2a-backend deepep \
+        --deepep-mode low_latency
+        NODE_RANK=$i
+        break
+    fi
+done
+```
+
+```shell Command
+# ============================================================
+# Before running, replace the following placeholders:
+#   <your prefill ip>: prefill node IP address
+#   <your decode ip>: decode node IP address
+# ============================================================
+
+python -m sglang_router.launch_router \
+    --pd-disaggregation \
+    --policy cache_aware \
+    --prefill http://<your prefill ip>:8000 8998 \
+    --decode http://<your decode ip>:8001 \
+    --host 127.0.0.1 \
+    --port 6688 \
+    --health-check-interval-secs 3600 --mini-lb
+```
+
+#### Benchmark
+
+We tested it based on the `RANDOM` dataset.
+
+```shell Command
+python -m sglang.bench_serving \
+    --dataset-name random \
+    --backend sglang \
+    --host 127.0.0.1 \
+    --port 6688 \
+    --max-concurrency 32 \
+    --random-input-len 16000 \
+    --random-output-len 1000 \
+    --num-prompts 128 \
+    --random-range-ratio 1 \
+    --request-rate inf
+```
+
+### MiMo-V2-Flash 1P1D 12P IN32K OUT1 TTFT 5s
+
+**Model**: MiMo-V2-Flash
+
+**Hardware**: Atlas 800I A3
+
+**Cards**: 12
+
+**Deploy Mode**: PD Disaggregation
+
+**Quantization**: W8A8 INT8
+
+**Dataset**: 32K+1
+
+**TTFT**: 5s
+
+#### Model Deployment
+
+```bash Command
+# ============================================================
+# Before running, update the following variables:
+#   P_IP: prefill node IP address
+#   D_IP: decode node IP address
+#   ASCEND_MF_STORE_URL: prefill node IP with port
+#   MODEL_PATH: path to the model weights directory
+#   HCCL_SOCKET_IFNAME: network interface name for HCCL
+#   GLOO_SOCKET_IFNAME: network interface name for Gloo
+# ============================================================
+
+
+echo performance | tee /sys/devices/system/cpu/cpu*/cpufreq/scaling_governor
+sysctl -w vm.swappiness=0
+sysctl -w kernel.numa_balancing=0
+sysctl -w kernel.sched_migration_cost_ns=50000
+
+unset https_proxy
+unset http_proxy
+unset HTTPS_PROXY
+unset HTTP_PROXY
+unset ASCEND_LAUNCH_BLOCKING
+
+source /usr/local/Ascend/ascend-toolkit/set_env.sh
+source /usr/local/Ascend/nnal/atb/set_env.sh
+
+export ASCEND_USE_FIA=1
+export DEEPEP_NORMAL_LONG_SEQ_PER_ROUND_TOKENS=3584
+export DEEPEP_NORMAL_LONG_SEQ_ROUND=32
+export DEEP_NORMAL_MODE_USE_INT8_QUANT=1
+export HCCL_CONNECT_TIMEOUT=1800
+export HCCL_OP_EXPANSION_MODE=AIV
+export PYTORCH_NPU_ALLOC_CONF=expandable_segments:True
+export SGLANG_DEEPEP_BF16_DISPATCH=0
+export SGLANG_DISAGGREGATION_BOOTSTRAP_TIMEOUT=3600
+export SGLANG_DISAGGREGATION_WAITING_TIMEOUT=3600
+export SGLANG_ENABLE_OVERLAP_PLAN_STREAM=0
+export SGLANG_ENABLE_SPEC_V2=1
+export SGLANG_SET_CPU_AFFINITY=1
+export STREAMS_PER_DEVICE=32
+
+P_IP=('<your prefill ip>')
+D_IP=('<your decode ip>')
+
+export ASCEND_MF_STORE_URL="tcp://<your prefill ip>:24670"
+
+MODEL_PATH=/path/to/model-weights
+
+LOCAL_HOST1=`hostname -I|awk -F " " '{print$1}'`
+LOCAL_HOST2=`hostname -I|awk -F " " '{print$2}'`
+echo "${LOCAL_HOST1}"
+echo "${LOCAL_HOST2}"
+# prefill
+for i in "${!P_IP[@]}";
+do
+    if [[ "$LOCAL_HOST1" == "${P_IP[$i]}" || "$LOCAL_HOST2" == "${P_IP[$i]}" ]];
+    then
+        echo "${P_IP[$i]}"
+        export GLOO_SOCKET_IFNAME=<network-interface>
+        export HCCL_BUFFSIZE=1024
+        export HCCL_SOCKET_IFNAME=<network-interface>
+        export SGLANG_DEEPEP_NUM_MAX_DISPATCH_TOKENS_PER_RANK=32
+        export SGLANG_DISAGGREGATION_FORCE_QUERY_PREFILL_DP_RANK=1
+
+        python3 -m sglang.launch_server \
+        --model-path ${MODEL_PATH} \
+        --disaggregation-mode prefill \
+        --host ${P_IP[$i]} \
+        --port 8000 \
+        --disaggregation-bootstrap-port 8998 \
+        --node-rank 0 \
+        --attention-backend ascend \
+        --device npu \
+        --tp-size 8 \
+        --nnodes 1 \
+        --chunked-prefill-size 8192 \
+        --trust-remote-code \
+        --max-running-requests 64 \
+        --mem-fraction-static 0.8 \
+        --swa-full-tokens-ratio 0.3 \
+        --disaggregation-transfer-backend ascend \
+        --disable-radix-cache \
+        --disable-cuda-graph \
+        --disable-piecewise-cuda-graph \
+        --dp-size 2
+        NODE_RANK=$i
+        break
+    fi
+done
+
+# decode
+for i in "${!D_IP[@]}";
+do
+    if [[ "$LOCAL_HOST1" == "${D_IP[$i]}" || "$LOCAL_HOST2" == "${D_IP[$i]}" ]];
+    then
+        echo "${D_IP[$i]}"
+        export GLOO_SOCKET_IFNAME=<network-interface>
+        export HCCL_BUFFSIZE=800
+        export HCCL_SOCKET_IFNAME=<network-interface>
+        export SGLANG_DEEPEP_NUM_MAX_DISPATCH_TOKENS_PER_RANK=128
+
+        python3 -m sglang.launch_server \
+        --model-path ${MODEL_PATH} \
+        --disaggregation-mode decode \
+        --host ${D_IP[$i]} \
+        --port 8001 \
+        --attention-backend ascend \
+        --device npu \
+        --tp-size 16 \
+        --nnodes 1 \
+        --trust-remote-code \
+        --max-running-requests 64 \
+        --mem-fraction-static 0.8 \
+        --swa-full-tokens-ratio 0.3 \
+        --cuda-graph-bs 1 2 4 8 12 16 20 24 28 32 \
+        --disaggregation-transfer-backend ascend \
+        --speculative-algorithm EAGLE \
+        --speculative-num-steps 3 \
+        --speculative-eagle-topk 1 \
+        --speculative-num-draft-tokens 4 \
+        --enable-multi-layer-eagle \
+        --disable-radix-cache \
+        --dp-size 2 \
+        --enable-dp-attention \
+        --enable-dp-lm-head \
+        --moe-a2a-backend deepep \
+        --deepep-mode low_latency
+        NODE_RANK=$i
+        break
+    fi
+done
+```
+
+```shell Command
+# ============================================================
+# Before running, replace the following placeholders:
+#   <your prefill ip>: prefill node IP address
+#   <your decode ip>: decode node IP address
+# ============================================================
+
+python -m sglang_router.launch_router \
+    --pd-disaggregation \
+    --policy cache_aware \
+    --prefill http://<your prefill ip>:8000 8998 \
+    --decode http://<your decode ip>:8001 \
+    --host 127.0.0.1 \
+    --port 6688 \
+    --health-check-interval-secs 3600 --mini-lb
+```
+
+#### Benchmark
+
+We tested it based on the `RANDOM` dataset.
+
+```shell Command
+python -m sglang.bench_serving \
+    --dataset-name random \
+    --backend sglang \
+    --host 127.0.0.1 \
+    --port 6688 \
+    --max-concurrency 64 \
+    --random-input-len 32000 \
+    --random-output-len 1 \
+    --num-prompts 128 \
+    --random-range-ratio 1 \
+    --request-rate 0.4
+```
+
+### MiMo-V2-Flash 1P1D 12P IN32K OUT1K TPOT 20ms
+
+**Model**: MiMo-V2-Flash
+
+**Hardware**: Atlas 800I A3
+
+**Cards**: 12
+
+**Deploy Mode**: PD Disaggregation
+
+**Quantization**: W8A8 INT8
+
+**Dataset**: 32K+1K
+
+**TPOT**: 20ms
+
+#### Model Deployment
+
+```bash Command
+# ============================================================
+# Before running, update the following variables:
+#   P_IP: prefill node IP address
+#   D_IP: decode node IP address
+#   ASCEND_MF_STORE_URL: prefill node IP with port
+#   MODEL_PATH: path to the model weights directory
+#   HCCL_SOCKET_IFNAME: network interface name for HCCL
+#   GLOO_SOCKET_IFNAME: network interface name for Gloo
+# ============================================================
+
+
+echo performance | tee /sys/devices/system/cpu/cpu*/cpufreq/scaling_governor
+sysctl -w vm.swappiness=0
+sysctl -w kernel.numa_balancing=0
+sysctl -w kernel.sched_migration_cost_ns=50000
+
+unset https_proxy
+unset http_proxy
+unset HTTPS_PROXY
+unset HTTP_PROXY
+unset ASCEND_LAUNCH_BLOCKING
+
+source /usr/local/Ascend/ascend-toolkit/set_env.sh
+source /usr/local/Ascend/nnal/atb/set_env.sh
+
+export ASCEND_USE_FIA=1
+export DEEPEP_NORMAL_LONG_SEQ_PER_ROUND_TOKENS=3584
+export DEEPEP_NORMAL_LONG_SEQ_ROUND=32
+export DEEP_NORMAL_MODE_USE_INT8_QUANT=1
+export HCCL_CONNECT_TIMEOUT=1800
+export HCCL_OP_EXPANSION_MODE=AIV
+export PYTORCH_NPU_ALLOC_CONF=expandable_segments:True
+export SGLANG_DEEPEP_BF16_DISPATCH=0
+export SGLANG_DISAGGREGATION_BOOTSTRAP_TIMEOUT=3600
+export SGLANG_DISAGGREGATION_WAITING_TIMEOUT=3600
+export SGLANG_ENABLE_OVERLAP_PLAN_STREAM=0
+export SGLANG_ENABLE_SPEC_V2=1
+export SGLANG_SET_CPU_AFFINITY=1
+export STREAMS_PER_DEVICE=32
+
+P_IP=('<your prefill ip>')
+D_IP=('<your decode ip>')
+
+export ASCEND_MF_STORE_URL="tcp://<your prefill ip>:24670"
+
+MODEL_PATH=/path/to/model-weights
+
+LOCAL_HOST1=`hostname -I|awk -F " " '{print$1}'`
+LOCAL_HOST2=`hostname -I|awk -F " " '{print$2}'`
+echo "${LOCAL_HOST1}"
+echo "${LOCAL_HOST2}"
+# prefill
+for i in "${!P_IP[@]}";
+do
+    if [[ "$LOCAL_HOST1" == "${P_IP[$i]}" || "$LOCAL_HOST2" == "${P_IP[$i]}" ]];
+    then
+        echo "${P_IP[$i]}"
+        export GLOO_SOCKET_IFNAME=<network-interface>
+        export HCCL_BUFFSIZE=1024
+        export HCCL_SOCKET_IFNAME=<network-interface>
+        export SGLANG_DEEPEP_NUM_MAX_DISPATCH_TOKENS_PER_RANK=32
+        export SGLANG_DISAGGREGATION_FORCE_QUERY_PREFILL_DP_RANK=1
+
+        python3 -m sglang.launch_server \
+        --model-path ${MODEL_PATH} \
+        --disaggregation-mode prefill \
+        --host ${P_IP[$i]} \
+        --port 8000 \
+        --disaggregation-bootstrap-port 8998 \
+        --node-rank 0 \
+        --attention-backend ascend \
+        --device npu \
+        --tp-size 8 \
+        --nnodes 1 \
+        --chunked-prefill-size 8192 \
+        --trust-remote-code \
+        --max-running-requests 64 \
+        --mem-fraction-static 0.8 \
+        --swa-full-tokens-ratio 0.3 \
+        --disaggregation-transfer-backend ascend \
+        --disable-radix-cache \
+        --disable-cuda-graph \
+        --disable-piecewise-cuda-graph \
+        --dp-size 2
+        NODE_RANK=$i
+        break
+    fi
+done
+
+# decode
+for i in "${!D_IP[@]}";
+do
+    if [[ "$LOCAL_HOST1" == "${D_IP[$i]}" || "$LOCAL_HOST2" == "${D_IP[$i]}" ]];
+    then
+        echo "${D_IP[$i]}"
+        export GLOO_SOCKET_IFNAME=<network-interface>
+        export HCCL_BUFFSIZE=800
+        export HCCL_SOCKET_IFNAME=<network-interface>
+        export SGLANG_DEEPEP_NUM_MAX_DISPATCH_TOKENS_PER_RANK=128
+
+        python3 -m sglang.launch_server \
+        --model-path ${MODEL_PATH} \
+        --disaggregation-mode decode \
+        --host ${D_IP[$i]} \
+        --port 8001 \
+        --attention-backend ascend \
+        --device npu \
+        --tp-size 16 \
+        --nnodes 1 \
+        --trust-remote-code \
+        --max-running-requests 64 \
+        --mem-fraction-static 0.8 \
+        --swa-full-tokens-ratio 0.3 \
+        --cuda-graph-bs 1 2 4 8 12 16 20 24 28 32 \
+        --disaggregation-transfer-backend ascend \
+        --speculative-algorithm EAGLE \
+        --speculative-num-steps 3 \
+        --speculative-eagle-topk 1 \
+        --speculative-num-draft-tokens 4 \
+        --enable-multi-layer-eagle \
+        --disable-radix-cache \
+        --dp-size 2 \
+        --enable-dp-attention \
+        --enable-dp-lm-head \
+        --moe-a2a-backend deepep \
+        --deepep-mode low_latency
+        NODE_RANK=$i
+        break
+    fi
+done
+```
+
+```shell Command
+# ============================================================
+# Before running, replace the following placeholders:
+#   <your prefill ip>: prefill node IP address
+#   <your decode ip>: decode node IP address
+# ============================================================
+
+python -m sglang_router.launch_router \
+    --pd-disaggregation \
+    --policy cache_aware \
+    --prefill http://<your prefill ip>:8000 8998 \
+    --decode http://<your decode ip>:8001 \
+    --host 127.0.0.1 \
+    --port 6688 \
+    --health-check-interval-secs 3600 --mini-lb
+```
+
+#### Benchmark
+
+We tested it based on the `RANDOM` dataset.
+
+```shell Command
+python -m sglang.bench_serving \
+    --dataset-name random \
+    --backend sglang \
+    --host 127.0.0.1 \
+    --port 6688 \
+    --max-concurrency 64 \
+    --random-input-len 32000 \
+    --random-output-len 1000 \
+    --num-prompts 128 \
+    --random-range-ratio 1 \
+    --request-rate inf
+```

docs_new/docs/hardware-platforms/ascend-npus/best_practice/minimax_m2_5.mdx

@@ -115,7 +115,9 @@ python3 -m sglang.launch_server \
     --speculative-draft-model-quantization unquant \
     --dtype bfloat16 \
     --trust-remote-code \
-    --tokenizer-worker-num 4
+    --tokenizer-worker-num 4 \
+    --reasoning-parser minimax-append-think \
+    --tool-call-parser minimax-m2
 ```
 
 #### Benchmark
@@ -206,7 +208,7 @@ python3 -m sglang.launch_server \
     --enable-prefill-delayer \
     --prefill-max-requests 10 \
     --chunked-prefill-size 67072 \
-    --max-prefill-token 67000 \
+    --max-prefill-tokens 67000 \
     --cuda-graph-bs 2 4 8 12 16 18 20 22 24 26 \
     --moe-a2a-backend ascend_fuseep \
     --deepep-mode auto \
@@ -317,7 +319,7 @@ python3 -m sglang.launch_server \
     --enable-prefill-delayer \
     --prefill-max-requests 4 \
     --chunked-prefill-size 160000 \
-    --max-prefill-token 80000 \
+    --max-prefill-tokens 80000 \
     --cuda-graph-bs 2 4 6 8 \
     --moe-a2a-backend ascend_fuseep \
     --deepep-mode auto \
@@ -429,7 +431,7 @@ python3 -m sglang.launch_server \
     --enable-prefill-delayer \
     --prefill-max-requests 3 \
     --chunked-prefill-size -1 \
-    --max-prefill-token 8192 \
+    --max-prefill-tokens 8192 \
     --cuda-graph-bs 1 2 3 4 5 6 \
     --moe-a2a-backend ascend_fuseep \
     --deepep-mode auto \
@@ -533,7 +535,7 @@ python3 -m sglang.launch_server \
     --prefill-delayer-max-delay-passes 500 \
     --enable-prefill-delayer \
     --chunked-prefill-size -1 \
-    --max-prefill-token 8192 \
+    --max-prefill-tokens 8192 \
     --cuda-graph-bs 1 2 4 8 12 16 20 \
     --moe-a2a-backend ascend_fuseep \
     --deepep-mode auto \

docs_new/docs/hardware-platforms/ascend-npus/best_practice/qwen3-8b.mdx

@@ -101,7 +101,9 @@ python3 -m sglang.launch_server \
     --speculative-draft-model-path $DRAFT_MODEL_PATH \
     --speculative-num-steps 3 \
     --speculative-eagle-topk 1 \
-    --speculative-num-draft-tokens 4
+    --speculative-num-draft-tokens 4 \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen
 ```
 
 #### Benchmark
@@ -195,7 +197,9 @@ python3 -m sglang.launch_server \
     --speculative-draft-model-path $DRAFT_MODEL_PATH \
     --speculative-num-steps 4 \
     --speculative-eagle-topk 1 \
-    --speculative-num-draft-tokens 5
+    --speculative-num-draft-tokens 5 \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen
 ```
 
 #### Benchmark
@@ -289,7 +293,9 @@ python3 -m sglang.launch_server \
     --speculative-draft-model-path $DRAFT_MODEL_PATH \
     --speculative-num-steps 4 \
     --speculative-eagle-topk 1 \
-    --speculative-num-draft-tokens 5
+    --speculative-num-draft-tokens 5 \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen
 ```
 
 #### Benchmark

docs_new/docs/hardware-platforms/ascend-npus/best_practice/qwen3_235b_a22b.mdx

@@ -99,7 +99,9 @@ python3 -m sglang.launch_server \
     --enable-dp-lm-head \
     --tp 16 \
     --mem-fraction-static 0.78 \
-    --cuda-graph-bs 1
+    --cuda-graph-bs 1 \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen25
 ```
 
 #### Benchmark
@@ -173,8 +175,6 @@ export SGLANG_DISAGGREGATION_BOOTSTRAP_TIMEOUT=600
 export SGLANG_ENABLE_OVERLAP_PLAN_STREAM=1
 export SGLANG_ENABLE_SPEC_V2=1
 export SGLANG_NPU_FUSED_MOE_MODE=2
-export SGLANG_NPU_PROFILING=0
-export SGLANG_NPU_PROFILING_BS=27
 export SGLANG_PREFILL_DELAYER_MAX_DELAY_PASSES=100
 export SGLANG_SCHEDULER_DECREASE_PREFILL_IDLE=1
 
@@ -207,7 +207,9 @@ python3 -m sglang.launch_server \
     --enable-dp-attention \
     --enable-dp-lm-head \
     --mem-fraction-static 0.8 \
-    --cuda-graph-bs 1 2 4 8 16 20 24 26 27
+    --cuda-graph-bs 1 2 4 8 16 20 24 26 27 \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen25
 ```
 
 #### Benchmark

docs_new/docs/hardware-platforms/ascend-npus/best_practice/qwen3_30b_a3b.mdx

@@ -108,7 +108,9 @@ python3 -m sglang.launch_server \
     --dp-size 2 \
     --mem-fraction-static 0.85 \
     --cuda-graph-bs 1 2 4 8 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80 84 \
-    --dtype bfloat16
+    --dtype bfloat16 \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen
 ```
 
 #### Benchmark
@@ -206,7 +208,9 @@ python3 -m sglang.launch_server \
     --tp-size 2 \
     --mem-fraction-static 0.87 \
     --cuda-graph-bs 1 5 15 40 70 100 120 130 140 146 150 154 156 158 160 162 \
-    --dtype bfloat16
+    --dtype bfloat16 \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen
 ```
 
 #### Benchmark
@@ -304,7 +308,9 @@ python3 -m sglang.launch_server \
     --tp-size 2 \
     --mem-fraction-static 0.87 \
     --cuda-graph-bs 1 5 15 40 70 100 120 130 140 146 150 154 156 158 160 162 \
-    --dtype bfloat16
+    --dtype bfloat16 \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen
 ```
 
 #### Benchmark
@@ -401,7 +407,9 @@ python3 -m sglang.launch_server \
     --tp-size 2 \
     --mem-fraction-static 0.6 \
     --cuda-graph-bs 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 \
-    --dtype bfloat16
+    --dtype bfloat16 \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen
 ```
 
 #### Benchmark

docs_new/docs/hardware-platforms/ascend-npus/best_practice/qwen3_32b.mdx

@@ -100,7 +100,9 @@ python3 -m sglang.launch_server \
     --tp-size 16 \
     --mem-fraction-static 0.72 \
     --cuda-graph-bs 1 \
-    --dtype bfloat16
+    --dtype bfloat16 \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen
 ```
 
 #### Benchmark
@@ -197,7 +199,9 @@ python3 -m sglang.launch_server \
     --tp-size 4 \
     --mem-fraction-static 0.845 \
     --cuda-graph-bs 16 32 64 72 88 90 92 94 96 97 98 99 100 101 \
-    --dtype bfloat16
+    --dtype bfloat16 \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen
 ```
 
 #### Benchmark
@@ -294,7 +298,9 @@ python3 -m sglang.launch_server \
     --tp-size 4 \
     --mem-fraction-static 0.845 \
     --cuda-graph-bs 16 32 64 72 88 90 92 94 96 97 98 99 100 101 \
-    --dtype bfloat16
+    --dtype bfloat16 \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen
 ```
 
 #### Benchmark

docs_new/docs/hardware-platforms/ascend-npus/best_practice/qwen3_5_397b.mdx

@@ -119,7 +119,9 @@ python3 -m sglang.launch_server \
     --speculative-num-steps 3 \
     --speculative-eagle-topk 1 \
     --speculative-num-draft-tokens 4 \
-    --speculative-draft-model-quantization unquant
+    --speculative-draft-model-quantization unquant \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen3_coder
 ```
 
 #### Benchmark
@@ -228,7 +230,9 @@ python3 -m sglang.launch_server \
     --speculative-num-steps 3 \
     --speculative-eagle-topk 1 \
     --speculative-num-draft-tokens 4 \
-    --speculative-draft-model-quantization unquant
+    --speculative-draft-model-quantization unquant \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen3_coder
 ```
 
 #### Benchmark
@@ -297,20 +301,15 @@ export DEEPEP_NORMAL_LONG_SEQ_ROUND=32
 export DEEP_NORMAL_MODE_USE_INT8_QUANT=1
 export GDN_ATTN_BACKEND_TRITON=1
 export GLOO_SOCKET_IFNAME=<network-interface>
-export HCCL_BUFFSIZE=0
+export HCCL_BUFFSIZE=2200
 export HCCL_OP_EXPANSION_MODE=AIV
 export HCCL_SOCKET_IFNAME=<network-interface>
 export PYTORCH_NPU_ALLOC_CONF=expandable_segments:True
 export SGLANG_DEEPEP_NUM_MAX_DISPATCH_TOKENS_PER_RANK=128
 export SGLANG_ENABLE_OVERLAP_PLAN_STREAM=1
 export SGLANG_ENABLE_SPEC_V2=1
-export SGLANG_ENABLE_TP_MEMORY_INBALANCE_CHECK=0
 export SGLANG_SET_CPU_AFFINITY=1
-export SGLANG_ZBAL_BOOTSTRAP_URL=tcp://127.0.0.1:24669
-export SGLANG_ZBAL_LOCAL_MEM_SIZE=59648
 export STREAMS_PER_DEVICE=32
-export ZBAL_ENABLE_GRAPH=1
-export ZBAL_NPU_ALLOC_CONF=use_vmm_for_static_memory:True
 
 python3 -m sglang.launch_server \
     --model-path $MODEL_PATH \
@@ -326,7 +325,6 @@ python3 -m sglang.launch_server \
     --trust-remote-code \
     --max-running-requests 64 \
     --mem-fraction-static 0.6 \
-    --cuda-graph-bs 2 4 6 8 10 12 16 20 24 32 40 48 56 64 \
     --quantization modelslim \
     --enable-multimodal \
     --moe-a2a-backend deepep \
@@ -338,7 +336,9 @@ python3 -m sglang.launch_server \
     --speculative-num-steps 3 \
     --speculative-eagle-topk 1 \
     --speculative-num-draft-tokens 4 \
-    --speculative-draft-model-quantization unquant
+    --speculative-draft-model-quantization unquant \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen3_coder
 ```
 
 #### Benchmark
@@ -455,7 +455,9 @@ python3 -m sglang.launch_server \
     --speculative-num-steps 3 \
     --speculative-eagle-topk 1 \
     --speculative-num-draft-tokens 4 \
-    --speculative-draft-model-quantization unquant
+    --speculative-draft-model-quantization unquant \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen3_coder
 ```
 
 #### Benchmark
@@ -568,7 +570,9 @@ python3 -m sglang.launch_server \
     --speculative-num-steps 3 \
     --speculative-eagle-topk 1 \
     --speculative-num-draft-tokens 4 \
-    --speculative-draft-model-quantization unquant
+    --speculative-draft-model-quantization unquant \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen3_coder
 ```
 
 #### Benchmark
@@ -581,10 +585,10 @@ python -m sglang.bench_serving \
     --backend sglang \
     --host 127.0.0.1 \
     --port 6688 \
-    --max-concurrency 144 \
+    --max-concurrency 132 \
     --random-input-len 16384 \
     --random-output-len 1024 \
-    --num-prompts 144 \
+    --num-prompts 132 \
     --random-range-ratio 1 \
     --request-rate inf \
     --warmup-requests 8
@@ -680,7 +684,9 @@ python3 -m sglang.launch_server \
     --speculative-num-steps 3 \
     --speculative-eagle-topk 1 \
     --speculative-num-draft-tokens 4 \
-    --speculative-draft-model-quantization unquant
+    --speculative-draft-model-quantization unquant \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen3_coder
 ```
 
 #### Benchmark
@@ -792,7 +798,9 @@ python3 -m sglang.launch_server \
     --speculative-num-steps 3 \
     --speculative-eagle-topk 1 \
     --speculative-num-draft-tokens 4 \
-    --speculative-draft-model-quantization unquant
+    --speculative-draft-model-quantization unquant \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen3_coder
 ```
 
 #### Benchmark
@@ -905,7 +913,9 @@ python3 -m sglang.launch_server \
     --speculative-num-steps 3 \
     --speculative-eagle-topk 1 \
     --speculative-num-draft-tokens 4 \
-    --speculative-draft-model-quantization unquant
+    --speculative-draft-model-quantization unquant \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen3_coder
 ```
 
 #### Benchmark
@@ -918,13 +928,13 @@ python -m sglang.bench_serving \
     --backend sglang \
     --host 127.0.0.1 \
     --port 6688 \
-    --max-concurrency 8 \
+    --max-concurrency 6 \
     --random-input-len 65536 \
     --random-output-len 1024 \
-    --num-prompts 8 \
+    --num-prompts 6 \
     --random-range-ratio 1 \
     --request-rate inf \
-    --warmup-requests 8
+    --warmup-requests 6
 ```
 
 ### Qwen3.5-397B W4A8 8P IN64K OUT1K 50ms
@@ -1018,7 +1028,9 @@ python3 -m sglang.launch_server \
     --speculative-num-steps 3 \
     --speculative-eagle-topk 1 \
     --speculative-num-draft-tokens 4 \
-    --speculative-draft-model-quantization unquant
+    --speculative-draft-model-quantization unquant \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen3_coder
 ```
 
 #### Benchmark
@@ -1087,21 +1099,15 @@ export DEEPEP_NORMAL_LONG_SEQ_ROUND=20
 export DEEP_NORMAL_MODE_USE_INT8_QUANT=1
 export GDN_ATTN_BACKEND_TRITON=1
 export GLOO_SOCKET_IFNAME=<network-interface>
-export HCCL_BUFFSIZE=64
+export HCCL_BUFFSIZE=2200
 export HCCL_OP_EXPANSION_MODE=AIV
 export HCCL_SOCKET_IFNAME=<network-interface>
 export PYTORCH_NPU_ALLOC_CONF=expandable_segments:True
 export SGLANG_DEEPEP_NUM_MAX_DISPATCH_TOKENS_PER_RANK=128
 export SGLANG_ENABLE_OVERLAP_PLAN_STREAM=1
 export SGLANG_ENABLE_SPEC_V2=1
-export SGLANG_ENABLE_TP_MEMORY_INBALANCE_CHECK=0
 export SGLANG_SET_CPU_AFFINITY=1
-export SGLANG_ZBAL_BOOTSTRAP_URL=tcp://127.0.0.1:24669
-export SGLANG_ZBAL_LOCAL_MEM_SIZE=58672
 export STREAMS_PER_DEVICE=32
-export ZBAL_ENABLE_GRAPH=1
-export ZBAL_HCCL_OP=allreduce,_allgather_base,allgather,broadcast,scatter,reduce_scatter,_reduce_scatter_base,alltoall_base
-export ZBAL_NPU_ALLOC_CONF=use_vmm_for_static_memory:True
 
 python3 -m sglang.launch_server \
     --model-path $MODEL_PATH \
@@ -1117,7 +1123,6 @@ python3 -m sglang.launch_server \
     --max-running-requests 128 \
     --mem-fraction-static 0.6 \
     --max-total-tokens 1310720 \
-    --cuda-graph-bs 2 4 6 8 10 12 16 20 24 32 40 48 56 64 \
     --quantization modelslim \
     --enable-multimodal \
     --moe-a2a-backend deepep \
@@ -1132,7 +1137,9 @@ python3 -m sglang.launch_server \
     --speculative-num-steps 3 \
     --speculative-eagle-topk 1 \
     --speculative-num-draft-tokens 4 \
-    --speculative-draft-model-quantization unquant
+    --speculative-draft-model-quantization unquant \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen3_coder
 ```
 
 #### Benchmark

docs_new/docs/hardware-platforms/ascend-npus/best_practice/qwen3_6_27b.mdx

@@ -16,9 +16,9 @@ This page focuses on optimal configuration and benchmark results for Qwen3.6-27B
 | Qwen3.6-27B | Atlas 800I A3 | 1 | PD Mixed | 1080p_30+256 | 50ms | BF16 | [Optimal Configuration](#qwen3-6-27b-1p-in1080p-30-out256-50ms) |
 | Qwen3.6-27B | Atlas 800I A3 | 2 | PD Mixed | 64K+1K (90% prefix cache hit rate) | 50ms | BF16 | [Optimal Configuration](#qwen3-6-27b-2p-in64k-out1k-prefix90-50ms) |
 | Qwen3.6-27B | Atlas 800I A3 | 1 | PD Mixed | 3.5K+1.5K | 50ms | W8A8 INT8 | [Optimal Configuration](#qwen3-6-27b-w8a8-1p-in3k5-out1k5-50ms) |
+| Qwen3.6-27B | Atlas 800I A3 | 1 | PD Mixed | 64K+1K | 50ms | W8A8 INT8 | [Optimal Configuration](#qwen3-6-27b-w8a8-1p-in64k-out1k-50ms) |
 | Qwen3.6-27B | Atlas 800I A3 | 2 | PD Mixed | 128K+1K | 50ms | W8A8 INT8 | [Optimal Configuration](#qwen3-6-27b-w8a8-2p-in128k-out1k-50ms) |
 | Qwen3.6-27B | Atlas 800I A3 | 2 | PD Mixed | 16K+1K | 50ms | W8A8 INT8 | [Optimal Configuration](#qwen3-6-27b-w8a8-2p-in16k-out1k-50ms) |
-| Qwen3.6-27B | Atlas 800I A3 | 2 | PD Mixed | 64K+1K | 50ms | W8A8 INT8 | [Optimal Configuration](#qwen3-6-27b-w8a8-2p-in64k-out1k-50ms) |
 
 ## Optimal Configuration
 
@@ -74,8 +74,6 @@ export HCCL_SOCKET_IFNAME=<network-interface>
 export PYTORCH_NPU_ALLOC_CONF=expandable_segments:True
 export SGLANG_ENABLE_OVERLAP_PLAN_STREAM=1
 export SGLANG_ENABLE_SPEC_V2=1
-export SGLANG_NPU_PROFILING=1
-export SGLANG_NPU_PROFILING_STAGE=prefill
 export SGLANG_PREFILL_DELAYER_MAX_DELAY_PASSES=150
 export SGLANG_SCHEDULER_DECREASE_PREFILL_IDLE=1
 export SGLANG_SET_CPU_AFFINITY=1
@@ -105,7 +103,9 @@ python3 -m sglang.launch_server \
     --speculative-num-steps 3 \
     --speculative-eagle-topk 1 \
     --speculative-num-draft-tokens 4 \
-    --mm-enable-dp-encoder
+    --mm-enable-dp-encoder \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen3_coder
 ```
 
 #### Benchmark
@@ -173,8 +173,6 @@ export HCCL_SOCKET_IFNAME=<network-interface>
 export PYTORCH_NPU_ALLOC_CONF=expandable_segments:True
 export SGLANG_ENABLE_OVERLAP_PLAN_STREAM=1
 export SGLANG_ENABLE_SPEC_V2=1
-export SGLANG_NPU_PROFILING=1
-export SGLANG_NPU_PROFILING_STAGE=prefill
 export SGLANG_PREFILL_DELAYER_MAX_DELAY_PASSES=150
 export SGLANG_SCHEDULER_DECREASE_PREFILL_IDLE=1
 export SGLANG_SET_CPU_AFFINITY=1
@@ -204,7 +202,9 @@ python3 -m sglang.launch_server \
     --speculative-num-steps 3 \
     --speculative-eagle-topk 1 \
     --speculative-num-draft-tokens 4 \
-    --mm-enable-dp-encoder
+    --mm-enable-dp-encoder \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen3_coder
 ```
 
 #### Benchmark
@@ -288,18 +288,20 @@ python3 -m sglang.launch_server \
     --mamba-scheduler-strategy extra_buffer \
     --trust-remote-code \
     --max-running-requests 20 \
-    --max-mamba-cache-size 108 \
+    --max-mamba-cache-size 160 \
-    --mem-fraction-static 0.7 \
+    --mem-fraction-static 0.82 \
-    --cuda-graph-bs 1 2 4 8 12 15 17 19 20 \
+    --cuda-graph-bs 1 2 5 10 15 17 19 20 \
     --enable-prefill-delayer \
-    --prefill-delayer-queue-min-ratio 0.8 \
+    --prefill-delayer-queue-min-ratio 0.7 \
-    --prefill-delayer-max-delay-ms 30000 \
+    --prefill-delayer-max-delay-ms 20000 \
     --dtype bfloat16 \
     --mamba-ssm-dtype bfloat16 \
     --speculative-algorithm NEXTN \
     --speculative-num-steps 3 \
     --speculative-eagle-topk 1 \
-    --speculative-num-draft-tokens 4
+    --speculative-num-draft-tokens 4 \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen3_coder
 ```
 
 #### Benchmark
@@ -401,7 +403,9 @@ python3 -m sglang.launch_server \
     --speculative-algorithm NEXTN \
     --speculative-num-steps 3 \
     --speculative-eagle-topk 1 \
-    --speculative-num-draft-tokens 4
+    --speculative-num-draft-tokens 4 \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen3_coder
 ```
 
 #### Benchmark
@@ -421,6 +425,98 @@ python -m sglang.bench_serving \
     --random-range-ratio 1
 ```
 
+### Qwen3.6-27B W8A8 1P IN64K OUT1K 50ms
+
+**Model**: Qwen3.6-27B
+
+**Hardware**: Atlas 800I A3
+
+**Cards**: 1
+
+**Deploy Mode**: PD Mixed
+
+**Quantization**: W8A8 INT8
+
+**Dataset**: 64K+1K
+
+**TPOT**: 50ms
+
+#### Model Deployment
+
+```bash Command
+# ============================================================
+# Before running, update the following variables:
+#   MODEL_PATH: path to the model weights directory
+#   HCCL_SOCKET_IFNAME: network interface name for HCCL
+#   GLOO_SOCKET_IFNAME: network interface name for Gloo
+# ============================================================
+
+MODEL_PATH=/path/to/model-weights
+echo performance | tee /sys/devices/system/cpu/cpu*/cpufreq/scaling_governor
+sysctl -w vm.swappiness=0
+sysctl -w kernel.numa_balancing=0
+sysctl -w kernel.sched_migration_cost_ns=50000
+
+unset https_proxy
+unset http_proxy
+unset HTTPS_PROXY
+unset HTTP_PROXY
+unset ASCEND_LAUNCH_BLOCKING
+
+source /usr/local/Ascend/ascend-toolkit/set_env.sh
+source /usr/local/Ascend/nnal/atb/set_env.sh
+
+export GLOO_SOCKET_IFNAME=<network-interface>
+export HCCL_OP_EXPANSION_MODE=AIV
+export HCCL_SOCKET_IFNAME=<network-interface>
+export SGLANG_ENABLE_OVERLAP_PLAN_STREAM=1
+export SGLANG_ENABLE_SPEC_V2=1
+export SGLANG_SET_CPU_AFFINITY=1
+export STREAMS_PER_DEVICE=32
+
+python3 -m sglang.launch_server \
+    --model-path $MODEL_PATH \
+    --host 127.0.0.1 --port 6688 \
+    --tp-size 2 \
+    --nnodes 1 \
+    --attention-backend ascend \
+    --device npu \
+    --chunked-prefill-size -1 \
+    --max-prefill-tokens 48000 \
+    --disable-radix-cache \
+    --trust-remote-code \
+    --max-running-requests 6 \
+    --max-mamba-cache-size 16 \
+    --mem-fraction-static 0.6 \
+    --cuda-graph-bs 1 2 4 5 6 \
+    --quantization modelslim \
+    --dtype bfloat16 \
+    --mamba-ssm-dtype bfloat16 \
+    --speculative-algorithm NEXTN \
+    --speculative-num-steps 3 \
+    --speculative-eagle-topk 1 \
+    --speculative-num-draft-tokens 4 \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen3_coder
+```
+
+#### Benchmark
+
+We tested it based on the `RANDOM` dataset.
+
+```shell Command
+python -m sglang.bench_serving \
+    --dataset-name random \
+    --backend sglang \
+    --host 127.0.0.1 \
+    --port 6688 \
+    --max-concurrency 6 \
+    --random-input-len 64000 \
+    --random-output-len 1000 \
+    --num-prompts 12 \
+    --random-range-ratio 1
+```
+
 ### Qwen3.6-27B W8A8 2P IN128K OUT1K 50ms
 
 **Model**: Qwen3.6-27B
@@ -493,7 +589,9 @@ python3 -m sglang.launch_server \
     --quantization modelslim \
     --mm-attention-backend ascend_attn \
     --dtype bfloat16 \
-    --mamba-ssm-dtype bfloat16
+    --mamba-ssm-dtype bfloat16 \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen3_coder
 ```
 
 #### Benchmark
@@ -587,7 +685,9 @@ python3 -m sglang.launch_server \
     --speculative-algorithm NEXTN \
     --speculative-num-steps 3 \
     --speculative-eagle-topk 1 \
-    --speculative-num-draft-tokens 4
+    --speculative-num-draft-tokens 4 \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen3_coder
 ```
 
 #### Benchmark
@@ -606,99 +706,3 @@ python -m sglang.bench_serving \
     --num-prompts 116 \
     --random-range-ratio 1
 ```
-
-### Qwen3.6-27B W8A8 2P IN64K OUT1K 50ms
-
-**Model**: Qwen3.6-27B
-
-**Hardware**: Atlas 800I A3
-
-**Cards**: 2
-
-**Deploy Mode**: PD Mixed
-
-**Quantization**: W8A8 INT8
-
-**Dataset**: 64K+1K
-
-**TPOT**: 50ms
-
-#### Model Deployment
-
-```bash Command
-# ============================================================
-# Before running, update the following variables:
-#   MODEL_PATH: path to the model weights directory
-#   HCCL_SOCKET_IFNAME: network interface name for HCCL
-#   GLOO_SOCKET_IFNAME: network interface name for Gloo
-# ============================================================
-
-MODEL_PATH=/path/to/model-weights
-echo performance | tee /sys/devices/system/cpu/cpu*/cpufreq/scaling_governor
-sysctl -w vm.swappiness=0
-sysctl -w kernel.numa_balancing=0
-sysctl -w kernel.sched_migration_cost_ns=50000
-
-unset https_proxy
-unset http_proxy
-unset HTTPS_PROXY
-unset HTTP_PROXY
-unset ASCEND_LAUNCH_BLOCKING
-
-source /usr/local/Ascend/ascend-toolkit/set_env.sh
-source /usr/local/Ascend/nnal/atb/set_env.sh
-
-export ASCEND_USE_FIA=1
-export GLOO_SOCKET_IFNAME=<network-interface>
-export HCCL_OP_EXPANSION_MODE=AIV
-export HCCL_SOCKET_IFNAME=<network-interface>
-export PYTORCH_NPU_ALLOC_CONF=expandable_segments:True
-export SGLANG_ENABLE_OVERLAP_PLAN_STREAM=1
-export SGLANG_ENABLE_SPEC_V2=1
-export SGLANG_PREFILL_DELAYER_MAX_DELAY_PASSES=30
-export SGLANG_SCHEDULER_DECREASE_PREFILL_IDLE=1
-export SGLANG_SET_CPU_AFFINITY=1
-export STREAMS_PER_DEVICE=32
-
-python3 -m sglang.launch_server \
-    --model-path $MODEL_PATH \
-    --host 127.0.0.1 --port 6688 \
-    --tp-size 4 \
-    --nnodes 1 \
-    --attention-backend ascend \
-    --device npu \
-    --chunked-prefill-size -1 \
-    --max-prefill-tokens 50000 \
-    --disable-radix-cache \
-    --trust-remote-code \
-    --max-running-requests 28 \
-    --max-mamba-cache-size 50 \
-    --mem-fraction-static 0.7 \
-    --cuda-graph-bs 2 4 6 \
-    --enable-multimodal \
-    --quantization modelslim \
-    --mm-attention-backend ascend_attn \
-    --dtype bfloat16 \
-    --mamba-ssm-dtype bfloat16 \
-    --speculative-algorithm NEXTN \
-    --speculative-num-steps 3 \
-    --speculative-eagle-topk 1 \
-    --speculative-num-draft-tokens 4
-```
-
-#### Benchmark
-
-We tested it based on the `RANDOM` dataset.
-
-```shell Command
-python -m sglang.bench_serving \
-    --dataset-name random \
-    --backend sglang \
-    --host 127.0.0.1 \
-    --port 6688 \
-    --max-concurrency 6 \
-    --random-input-len 64000 \
-    --random-output-len 1000 \
-    --num-prompts 24 \
-    --random-range-ratio 1
-```

docs_new/docs/hardware-platforms/ascend-npus/best_practice/qwen3_6_35b_a3b.mdx

@@ -108,7 +108,9 @@ python3 -m sglang.launch_server \
     --speculative-algorithm NEXTN \
     --speculative-num-steps 3 \
     --speculative-eagle-topk 1 \
-    --speculative-num-draft-tokens 4
+    --speculative-num-draft-tokens 4 \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen3_coder
 ```
 
 #### Benchmark
@@ -204,7 +206,9 @@ python3 -m sglang.launch_server \
     --speculative-algorithm NEXTN \
     --speculative-num-steps 3 \
     --speculative-eagle-topk 1 \
-    --speculative-num-draft-tokens 4
+    --speculative-num-draft-tokens 4 \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen3_coder
 ```
 
 #### Benchmark
@@ -287,12 +291,13 @@ python3 -m sglang.launch_server \
     --attention-backend ascend \
     --device npu \
     --chunked-prefill-size -1 \
+    --max-total-tokens 520960 \
     --max-prefill-tokens 128000 \
     --disable-radix-cache \
     --trust-remote-code \
     --max-running-requests 3 \
     --max-mamba-cache-size 10 \
-    --mem-fraction-static 0.63 \
+    --mem-fraction-static 0.9 \
     --cuda-graph-bs 1 2 3 \
     --enable-multimodal \
     --mm-attention-backend ascend_attn \
@@ -301,7 +306,9 @@ python3 -m sglang.launch_server \
     --speculative-algorithm NEXTN \
     --speculative-num-steps 3 \
     --speculative-eagle-topk 1 \
-    --speculative-num-draft-tokens 4
+    --speculative-num-draft-tokens 4 \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen3_coder
 ```
 
 #### Benchmark
@@ -396,7 +403,9 @@ python3 -m sglang.launch_server \
     --speculative-algorithm NEXTN \
     --speculative-num-steps 3 \
     --speculative-eagle-topk 1 \
-    --speculative-num-draft-tokens 4
+    --speculative-num-draft-tokens 4 \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen3_coder
 ```
 
 #### Benchmark
@@ -495,7 +504,9 @@ python3 -m sglang.launch_server \
     --speculative-algorithm NEXTN \
     --speculative-num-steps 3 \
     --speculative-eagle-topk 1 \
-    --speculative-num-draft-tokens 4
+    --speculative-num-draft-tokens 4 \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen3_coder
 ```
 
 #### Benchmark
@@ -575,13 +586,14 @@ python3 -m sglang.launch_server \
     --attention-backend ascend \
     --device npu \
     --chunked-prefill-size -1 \
+    --max-total-tokens 659840 \
     --max-prefill-tokens 43400 \
     --disable-radix-cache \
     --trust-remote-code \
     --prefill-max-requests 12 \
     --max-running-requests 122 \
     --max-mamba-cache-size 122 \
-    --mem-fraction-static 0.8 \
+    --mem-fraction-static 0.9 \
     --cuda-graph-bs 4 16 32 64 96 116 120 122 \
     --enable-multimodal \
     --mm-attention-backend ascend_attn \
@@ -590,7 +602,9 @@ python3 -m sglang.launch_server \
     --speculative-algorithm NEXTN \
     --speculative-num-steps 3 \
     --speculative-eagle-topk 1 \
-    --speculative-num-draft-tokens 4
+    --speculative-num-draft-tokens 4 \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen3_coder
 ```
 
 #### Benchmark
@@ -686,7 +700,9 @@ python3 -m sglang.launch_server \
     --speculative-algorithm NEXTN \
     --speculative-num-steps 3 \
     --speculative-eagle-topk 1 \
-    --speculative-num-draft-tokens 4
+    --speculative-num-draft-tokens 4 \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen3_coder
 ```
 
 #### Benchmark
@@ -767,12 +783,13 @@ python3 -m sglang.launch_server \
     --attention-backend ascend \
     --device npu \
     --chunked-prefill-size -1 \
+    --max-total-tokens 470784 \
     --max-prefill-tokens 65536 \
     --trust-remote-code \
     --mamba-scheduler-strategy extra_buffer \
     --max-running-requests 40 \
-    --max-mamba-cache-size 210 \
+    --max-mamba-cache-size 200 \
-    --mem-fraction-static 0.71 \
+    --mem-fraction-static 0.9 \
     --cuda-graph-bs 2 8 16 24 32 36 40 \
     --enable-multimodal \
     --mm-attention-backend ascend_attn \
@@ -781,7 +798,9 @@ python3 -m sglang.launch_server \
     --speculative-algorithm NEXTN \
     --speculative-num-steps 3 \
     --speculative-eagle-topk 1 \
-    --speculative-num-draft-tokens 4
+    --speculative-num-draft-tokens 4 \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen3_coder
 ```
 
 #### Benchmark
@@ -882,7 +901,9 @@ python3 -m sglang.launch_server \
     --speculative-num-steps 3 \
     --speculative-eagle-topk 1 \
     --speculative-num-draft-tokens 4 \
-    --context-length 1010000
+    --context-length 1010000 \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen3_coder
 ```
 
 #### Benchmark

docs_new/docs/hardware-platforms/ascend-npus/best_practice/qwen3_next_80b_a3b_instruct.mdx

@@ -116,7 +116,9 @@ python3 -m sglang.launch_server \
     --max-running-requests 2 \
     --cuda-graph-bs 2 \
     --mamba-ssm-dtype bfloat16 \
-    --speculative-draft-model-path $DRAFT_MODEL_PATH
+    --speculative-draft-model-path $DRAFT_MODEL_PATH \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen
 ```
 
 #### Benchmark
@@ -230,7 +232,9 @@ python3 -m sglang.launch_server \
     --enable-dp-lm-head \
     --moe-a2a-backend deepep \
     --deepep-mode auto \
-    --cuda-graph-bs 1 2 3 4 5 6 7 8 10 12 14 16 18 20 22 24 26 28 30 32 40 44 48 52 56 60 64 72 80 88 96 104 112 120 128 136 144 150
+    --cuda-graph-bs 1 2 3 4 5 6 7 8 10 12 14 16 18 20 22 24 26 28 30 32 40 44 48 52 56 60 64 72 80 88 96 104 112 120 128 136 144 150 \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen
 ```
 
 #### Benchmark
@@ -344,7 +348,9 @@ python3 -m sglang.launch_server \
     --max-running-requests 16 \
     --cuda-graph-bs 2 4 8 \
     --mamba-ssm-dtype bfloat16 \
-    --speculative-draft-model-path $DRAFT_MODEL_PATH
+    --speculative-draft-model-path $DRAFT_MODEL_PATH \
+    --reasoning-parser qwen3 \
+    --tool-call-parser qwen3_coder
 ```
 
 #### Benchmark