Add pr tests (#31952)

Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: sglang-npu-bot <sglangnpu@163.com>
Co-authored-by: Cherry_ming <136634645@qq.com>

.github/CODEOWNERS

@@ -90,7 +90,7 @@
 /sgl-model-gateway/examples/wasm @slin1237
 /test/registered/prefill_only @sundar24295s @chanh @fortunecookiee
 /benchmark/prefill_only/bench_score.py @sundar24295s @chanh @fortunecookiee
-/test/registered/ascend @ping1jing2 @ssshinigami  @e-martirosian
+/test/registered/npu @ping1jing2 @ssshinigami  @e-martirosian
 /test/srt/test_modelopt* @Edwardf0t1
 /python/sglang/srt/layers/gemma4_fused_ops.py @merrymercy @Ying1123 @Fridge003 @ispobock @HaiShaw @ch-wan @BBuf @Edwardf0t1 @kpham-sgl @pyc96
 /python/sglang/srt/function_call/gemma4_detector.py @CatherineSue @JustinTong0323 @kpham-sgl @pyc96

.github/workflows/nightly-test-npu.yml

@@ -114,8 +114,11 @@ jobs:
         test_config:
           - name: qwen3_32b_w8a8_2p_in3k5_out1k5_50ms_a2
             runner: linux-aarch64-a2-4
-            test_case: test/registered/ascend/performance/qwen3_32b/test_npu_qwen3_32b_w8a8_2p_in3k5_out1k5_50ms_a2.py
+            test_case: test/registered/npu/performance/qwen3_32b/test_npu_qwen3_32b_w8a8_2p_in3k5_out1k5_50ms_a2.py
             test_type: 'perf'
+          - name: qwen3_32b_w8a8_2p_in3k5_out1k5_50ms_gpqa_a2
+            runner: linux-aarch64-a2-4
+            test_case: test/registered/npu/accuracy/qwen3_32b/test_npu_qwen3_32b_w8a8_2p_in3k5_out1k5_50ms_gpqa_a2.py
     uses: ./.github/workflows/nightly-test-npu-e2e-single-node.yml
     with:
       runner: ${{ matrix.test_config.runner }}
@@ -138,119 +141,158 @@ jobs:
           # qwen3_6_35b_a3b performance tests
           - name: qwen3_6_35b_a3b_1p_in3k5_out1k5_50ms
             runner: linux-aarch64-a3-2
-            test_case: test/registered/ascend/performance/qwen3_6_35b_a3b/test_npu_qwen3_6_35b_a3b_1p_in3k5_out1k5_50ms.py
+            test_case: test/registered/npu/performance/qwen3_6_35b_a3b/test_npu_qwen3_6_35b_a3b_1p_in3k5_out1k5_50ms.py
             test_type: 'perf'
           - name: qwen3_6_35b_a3b_1p_aime26
             runner: linux-aarch64-a3-2
-            test_case: test/registered/ascend/accuracy/qwen3_6_35b_a3b/test_npu_qwen3_6_35b_a3b_1p_aime26.py
+            test_case: test/registered/npu/accuracy/qwen3_6_35b_a3b/test_npu_qwen3_6_35b_a3b_1p_aime26.py
           - name: qwen3_6_35b_a3b_1p_in64k_out1k_50ms
             runner: linux-aarch64-a3-2
-            test_case: test/registered/ascend/performance/qwen3_6_35b_a3b/test_npu_qwen3_6_35b_a3b_1p_in64k_out1k_50ms.py
+            test_case: test/registered/npu/performance/qwen3_6_35b_a3b/test_npu_qwen3_6_35b_a3b_1p_in64k_out1k_50ms.py
             test_type: 'perf'
           - name: qwen3_6_35b_a3b_1p_in128k_out1k_50ms
             runner: linux-aarch64-a3-2
-            test_case: test/registered/ascend/performance/qwen3_6_35b_a3b/test_npu_qwen3_6_35b_a3b_1p_in128k_out1k_50ms.py
+            test_case: test/registered/npu/performance/qwen3_6_35b_a3b/test_npu_qwen3_6_35b_a3b_1p_in128k_out1k_50ms.py
+            test_type: 'perf'
+          - name: qwen3_6_35b_a3b_1p_in64k_out1k_prefix90_50ms
+            runner: linux-aarch64-a3-2
+            test_case: test/registered/npu/performance/qwen3_6_35b_a3b/test_npu_qwen3_6_35b_a3b_1p_in64k_out1k_prefix90_50ms.py
             test_type: 'perf'
           - name: qwen3_6_35b_a3b_1p_in64k_out1k_prefix90_50ms_aime26
             runner: linux-aarch64-a3-2
-            test_case: test/registered/ascend/performance/qwen3_6_35b_a3b/test_npu_qwen3_6_35b_a3b_1p_in64k_out1k_prefix90_50ms_aime26.py
+            test_case: test/registered/npu/accuracy/qwen3_6_35b_a3b/test_npu_qwen3_6_35b_a3b_1p_in64k_out1k_prefix90_50ms_aime26.py
-            test_type: 'perf'
           - name: qwen3_6_35b_a3b_1p_in128k_out1k_prefix90_50ms
             runner: linux-aarch64-a3-2
-            test_case: test/registered/ascend/performance/qwen3_6_35b_a3b/test_npu_qwen3_6_35b_a3b_1p_in128k_out1k_prefix90_50ms.py
+            test_case: test/registered/npu/performance/qwen3_6_35b_a3b/test_npu_qwen3_6_35b_a3b_1p_in128k_out1k_prefix90_50ms.py
             test_type: 'perf'
           # qwen3_6_27b performance tests
+          - name: qwen3_6_27b_w8a8_1p_in3k5_out1k5_50ms
+            runner: linux-aarch64-a3-2
+            test_case: test/registered/npu/performance/qwen3_6_27b/test_npu_qwen3_6_27b_w8a8_1p_in3k5_out1k5_50ms.py
+            test_type: 'perf'
           - name: qwen3_6_27b_w8a8_1p_in3k5_out1k5_50ms_gpqa
             runner: linux-aarch64-a3-2
-            test_case: test/registered/ascend/performance/qwen3_6_27b/test_npu_qwen3_6_27b_w8a8_1p_in3k5_out1k5_50ms_gpqa.py
+            test_case: test/registered/npu/accuracy/qwen3_6_27b/test_npu_qwen3_6_27b_w8a8_1p_in3k5_out1k5_50ms_gpqa.py
-            test_type: 'perf'
           - name: qwen3_6_27b_w8a8_2p_in16k_out1k_50ms
             runner: linux-aarch64-a3-4
-            test_case: test/registered/ascend/performance/qwen3_6_27b/test_npu_qwen3_6_27b_w8a8_2p_in16k_out1k_50ms.py
+            test_case: test/registered/npu/performance/qwen3_6_27b/test_npu_qwen3_6_27b_w8a8_2p_in16k_out1k_50ms.py
             test_type: 'perf'
           - name: qwen3_6_27b_w8a8_1p_in64k_out1k_50ms
             runner: linux-aarch64-a3-4
-            test_case: test/registered/ascend/performance/qwen3_6_27b/test_npu_qwen3_6_27b_w8a8_1p_in64k_out1k_50ms.py
+            test_case: test/registered/npu/performance/qwen3_6_27b/test_npu_qwen3_6_27b_w8a8_1p_in64k_out1k_50ms.py
             test_type: 'perf'
           - name: qwen3_6_27b_w8a8_2p_in128k_out1k_50ms
             runner: linux-aarch64-a3-4
-            test_case: test/registered/ascend/performance/qwen3_6_27b/test_npu_qwen3_6_27b_w8a8_2p_in128k_out1k_50ms.py
+            test_case: test/registered/npu/performance/qwen3_6_27b/test_npu_qwen3_6_27b_w8a8_2p_in128k_out1k_50ms.py
             test_type: 'perf'
           - name: qwen3_6_27b_2p_in64k_out1k_prefix90_50ms
             runner: linux-aarch64-a3-4
-            test_case: test/registered/ascend/performance/qwen3_6_27b/test_npu_qwen3_6_27b_2p_in64k_out1k_prefix90_50ms.py
+            test_case: test/registered/npu/performance/qwen3_6_27b/test_npu_qwen3_6_27b_2p_in64k_out1k_prefix90_50ms.py
             test_type: 'perf'
           - name: qwen3_6_27b_1p_in1024x1024_30_out1024_50ms
             runner: linux-aarch64-a3-2
-            test_case: test/registered/ascend/performance/qwen3_6_27b/test_npu_qwen3_6_27b_1p_in1024x1024_30_out1024_50ms.py
+            test_case: test/registered/npu/performance/qwen3_6_27b/test_npu_qwen3_6_27b_1p_in1024x1024_30_out1024_50ms.py
             test_type: 'perf'
           - name: qwen3_6_27b_1p_in1080p_30_out256_50ms
             runner: linux-aarch64-a3-2
-            test_case: test/registered/ascend/performance/qwen3_6_27b/test_npu_qwen3_6_27b_1p_in1080p_30_out256_50ms.py
+            test_case: test/registered/npu/performance/qwen3_6_27b/test_npu_qwen3_6_27b_1p_in1080p_30_out256_50ms.py
             test_type: 'perf'
           - name: qwen3_6_27b_1p_gpqa
             runner: linux-aarch64-a3-2
-            test_case: test/registered/ascend/accuracy/qwen3_6_27b/test_npu_qwen3_6_27b_1p_gpqa.py
+            test_case: test/registered/npu/accuracy/qwen3_6_27b/test_npu_qwen3_6_27b_1p_gpqa.py
           # qwen3_32b performance tests
+          - name: qwen3_32b_w8a8_2p_in3k5_out1k5_50ms
+            runner: linux-aarch64-a3-4
+            test_case: test/registered/npu/performance/qwen3_32b/test_npu_qwen3_32b_w8a8_2p_in3k5_out1k5_50ms.py
+            test_type: 'perf'
           - name: qwen3_32b_w8a8_2p_in3k5_out1k5_50ms_gpqa
             runner: linux-aarch64-a3-4
-            test_case: test/registered/ascend/performance/qwen3_32b/test_npu_qwen3_32b_w8a8_2p_in3k5_out1k5_50ms_gpqa.py
+            test_case: test/registered/npu/accuracy/qwen3_32b/test_npu_qwen3_32b_w8a8_2p_in3k5_out1k5_50ms_gpqa.py
-            test_type: 'perf'
           - name: qwen3_32b_bf16_8p_in18k_out4k_6ms
             runner: linux-aarch64-a3-16
-            test_case: test/registered/ascend/performance/qwen3_32b/test_npu_qwen3_32b_bf16_8p_in18k_out4k_6ms.py
+            test_case: test/registered/npu/performance/qwen3_32b/test_npu_qwen3_32b_bf16_8p_in18k_out4k_6ms.py
             test_type: 'perf'
           - name: qwen3_32b_bf16_8p_gpqa
             runner: linux-aarch64-a3-16
-            test_case: test/registered/ascend/accuracy/qwen3_32b/test_npu_qwen3_32b_bf16_8p_gpqa.py
+            test_case: test/registered/npu/accuracy/qwen3_32b/test_npu_qwen3_32b_bf16_8p_gpqa.py
           # qwen3_30b_a3b performance tests
+          - name: qwen3_30b_w8a8_1p_in3k5_out1k5_50ms
+            runner: linux-aarch64-a3-2
+            test_case: test/registered/npu/performance/qwen3_30b_a3b/test_npu_qwen3_30b_w8a8_1p_in3k5_out1k5_50ms.py
+            test_type: 'perf'
           - name: qwen3_30b_w8a8_1p_in3k5_out1k5_50ms_aime25
             runner: linux-aarch64-a3-2
-            test_case: test/registered/ascend/performance/qwen3_30b_a3b/test_npu_qwen3_30b_w8a8_1p_in3k5_out1k5_50ms_aime25.py
+            test_case: test/registered/npu/accuracy/qwen3_30b_a3b/test_npu_qwen3_30b_w8a8_1p_in3k5_out1k5_50ms_aime25.py
-            test_type: 'perf'
           # qwen3-8b performance tests
+          - name: qwen3_8b_w8a8_1p_in3k5_out1k5_50ms
+            runner: linux-aarch64-a3-2
+            test_case: test/registered/npu/performance/qwen3-8b/test_npu_qwen3_8b_w8a8_1p_in3k5_out1k5_50ms.py
+            test_type: 'perf'
           - name: qwen3_8b_w8a8_1p_in3k5_out1k5_50ms_gpqa
             runner: linux-aarch64-a3-2
-            test_case: test/registered/ascend/performance/qwen3-8b/test_npu_qwen3_8b_w8a8_1p_in3k5_out1k5_50ms_gpqa.py
+            test_case: test/registered/npu/accuracy/qwen3-8b/test_npu_qwen3_8b_w8a8_1p_in3k5_out1k5_50ms_gpqa.py
+          - name: qwen3_8b_w8a8_1p_in6k_out1k5_bs16
+            runner: linux-aarch64-a3-2
+            test_case: test/registered/npu/performance/qwen3-8b/test_npu_qwen3_8b_w8a8_1p_in6k_out1k5_bs16.py
             test_type: 'perf'
           - name: qwen3_8b_w8a8_1p_in6k_out1k5_bs16_gpqa
             runner: linux-aarch64-a3-2
-            test_case: test/registered/ascend/performance/qwen3-8b/test_npu_qwen3_8b_w8a8_1p_in6k_out1k5_bs16_gpqa.py
+            test_case: test/registered/npu/accuracy/qwen3-8b/test_npu_qwen3_8b_w8a8_1p_in6k_out1k5_bs16_gpqa.py
-            test_type: 'perf'
           # qwen3_next_80b_a3b_instruct performance tests
+          - name: qwen3_next_80b_w8a8_2p_in6k_out1k5_bs16
+            runner: linux-aarch64-a3-4
+            test_case: test/registered/npu/performance/qwen3_next_80b_a3b_instruct/test_npu_qwen3_next_80b_w8a8_2p_in6k_out1k5_bs16.py
+            test_type: 'perf'
           - name: qwen3_next_80b_w8a8_2p_in6k_out1k5_bs16_aime25
             runner: linux-aarch64-a3-4
-            test_case: test/registered/ascend/performance/qwen3_next_80b_a3b_instruct/test_npu_qwen3_next_80b_w8a8_2p_in6k_out1k5_bs16_aime25.py
+            test_case: test/registered/npu/accuracy/qwen3_next_80b_a3b_instruct/test_npu_qwen3_next_80b_w8a8_2p_in6k_out1k5_bs16_aime25.py
-            test_type: 'perf'
           # minimax_m2_5 performance tests
+          - name: minimax_m2_5_w8a8_8p_in3k5_out1k5_50ms
+            runner: linux-aarch64-a3-16
+            test_case: test/registered/npu/performance/minimax_m2_5/test_npu_minimax_m2_5_w8a8_8p_in3k5_out1k5_50ms.py
+            test_type: 'perf'
           - name: minimax_m2_5_w8a8_8p_in3k5_out1k5_50ms_gpqa
             runner: linux-aarch64-a3-16
-            test_case: test/registered/ascend/performance/minimax_m2_5/test_npu_minimax_m2_5_w8a8_8p_in3k5_out1k5_50ms_gpqa.py
+            test_case: test/registered/npu/accuracy/minimax_m2_5/test_npu_minimax_m2_5_w8a8_8p_in3k5_out1k5_50ms_gpqa.py
+          - name: minimax_m2_5_w8a8_4p_in64k_out1k_prefix90_50ms
+            runner: linux-aarch64-a3-16
+            test_case: test/registered/npu/performance/minimax_m2_5/test_npu_minimax_m2_5_w8a8_4p_in64k_out1k_prefix90_50ms.py
             test_type: 'perf'
           - name: minimax_m2_5_w8a8_4p_in64k_out1k_prefix90_50ms_gpqa
             runner: linux-aarch64-a3-16
-            test_case: test/registered/ascend/performance/minimax_m2_5/test_npu_minimax_m2_5_w8a8_4p_in64k_out1k_prefix90_50ms_gpqa.py
+            test_case: test/registered/npu/accuracy/minimax_m2_5/test_npu_minimax_m2_5_w8a8_4p_in64k_out1k_prefix90_50ms_gpqa.py
-            test_type: 'perf'
           # deepseek_v3_2 accuracy tests
           - name: deepseek_v3_2_8p_aime25
             runner: linux-aarch64-a3-16
-            test_case: test/registered/ascend/accuracy/deepseek_v3_2/test_npu_deepseek_v3_2_8p_aime25.py
+            test_case: test/registered/npu/accuracy/deepseek_v3_2/test_npu_deepseek_v3_2_8p_aime25.py
           # glm4_7_flash accuracy tests
           - name: glm4_7_flash_1p_aime25
             runner: linux-aarch64-a3-2
-            test_case: test/registered/ascend/accuracy/glm4_7_flash/test_npu_glm4_7_flash_1p_aime25.py
+            test_case: test/registered/npu/accuracy/glm4_7_flash/test_npu_glm4_7_flash_1p_aime25.py
           # qwen3_vl_8b_thinking accuracy tests
           - name: qwen3_vl_8b_thinking_1p_mmmu
             runner: linux-aarch64-a3-2
-            test_case: test/registered/ascend/accuracy/qwen3_vl_8b_thinking/test_npu_qwen3_vl_8b_thinking_1p_mmmu.py
+            test_case: test/registered/npu/accuracy/qwen3_vl_8b_thinking/test_npu_qwen3_vl_8b_thinking_1p_mmmu.py
           # qwen3_vl_30b_a3b_thinking accuracy tests
           - name: qwen3_vl_30b_a3b_thinking_1p_mmmu
             runner: linux-aarch64-a3-2
-            test_case: test/registered/ascend/accuracy/qwen3_vl_30b_a3b_thinking/test_npu_qwen3_vl_30b_a3b_thinking_1p_mmmu.py
+            test_case: test/registered/npu/accuracy/qwen3_vl_30b_a3b_thinking/test_npu_qwen3_vl_30b_a3b_thinking_1p_mmmu.py
+          - name: qwen3_235b_w8a8_8p_in3k5_out1k5_50ms
+            runner: linux-aarch64-a3-16
+            test_case: test/registered/npu/performance/qwen3_235b_a22b/test_npu_qwen3_235b_w8a8_8p_in3k5_out1k5_50ms.py
+            test_type: 'perf'
+          - name: qwen3_5_397b_w4a8_8p_in3k5_out1k5_50ms
+            runner: linux-aarch64-a3-16
+            test_case: test/registered/npu/performance/qwen3_5_397b/test_npu_qwen3_5_397b_w4a8_8p_in3k5_out1k5_50ms.py
+            test_type: 'perf'
+          - name: kimi_k2_6_w4a8_8p_in3k5_out1k5_20ms
+            runner: linux-aarch64-a3-16
+            test_case: test/registered/npu/performance/kimi_k2_6/test_npu_kimi_k2_6_w4a8_8p_in3k5_out1k5_20ms.py
+            test_type: 'perf'
           # deepseek_v4_flash performance tests
           - name: deepseek_v4_flash_w8a8_8p_in8k_out1k_50ms
             runner: linux-aarch64-a3-16
-            test_case: test/registered/ascend/performance/deepseek_v4_flash/test_npu_deepseek_v4_flash_w8a8_8p_in8k_out1k_50ms.py
+            test_case: test/registered/npu/performance/deepseek_v4_flash/test_npu_deepseek_v4_flash_w8a8_8p_in8k_out1k_50ms.py
             test_type: 'perf'
     uses: ./.github/workflows/nightly-test-npu-e2e-single-node.yml
     with:
@@ -272,26 +314,32 @@ jobs:
       matrix:
         test_config:
           # glm5_1 performance tests
+          - name: glm5_1_w4a8_1p1d_32p_in64k_out1k_50ms
+            prefill_size: 2
+            decode_size: 2
+            router_size: 1
+            test_case: test/registered/npu/performance/glm5_1/test_npu_glm5_1_w4a8_1p1d_32p_in64k_out1k_50ms.py
+            test_type: 'perf'
+            prefill_decode_deployment: 'separation'
           - name: glm5_1_w4a8_1p1d_32p_in64k_out1k_50ms_aime26
             prefill_size: 2
             decode_size: 2
             router_size: 1
-            test_case: test/registered/ascend/performance/glm5_1/test_npu_glm5_1_w4a8_1p1d_32p_in64k_out1k_50ms_aime26.py
+            test_case: test/registered/npu/accuracy/glm5_1/test_npu_glm5_1_w4a8_1p1d_32p_in64k_out1k_50ms_aime26.py
-            test_type: 'perf'
             prefill_decode_deployment: 'separation'
           # mimo_v2_flash performance tests
           - name: test_npu_mimo_v2_flash_1p1d_12p_in16k_out1_ttft_5s
             prefill_size: 1
             decode_size: 1
             router_size: 1
-            test_case: test/registered/ascend/performance/mimo_v2_flash/test_npu_mimo_v2_flash_1p1d_12p_in16k_out1_ttft_5s.py
+            test_case: test/registered/npu/performance/mimo_v2_flash/test_npu_mimo_v2_flash_1p1d_12p_in16k_out1_ttft_5s.py
             test_type: 'perf'
             prefill_decode_deployment: 'separation'
           - name: test_npu_mimo_v2_flash_1p1d_12p_in16k_out1k_tpot_20ms
             prefill_size: 1
             decode_size: 1
             router_size: 1
-            test_case: test/registered/ascend/performance/mimo_v2_flash/test_npu_mimo_v2_flash_1p1d_12p_in16k_out1k_tpot_20ms.py
+            test_case: test/registered/npu/performance/mimo_v2_flash/test_npu_mimo_v2_flash_1p1d_12p_in16k_out1k_tpot_20ms.py
             test_type: 'perf'
             prefill_decode_deployment: 'separation'
     uses: ./.github/workflows/nightly-test-npu-e2e-multi-node.yml
@@ -318,10 +366,13 @@ jobs:
       matrix:
         test_config:
           # kimi_k2_6 performance tests
+          - name: kimi_k2_6_w4a8_16p_in64k_out1k_100ms
+            node_size: 2
+            test_case: test/registered/npu/performance/kimi_k2_6/test_npu_kimi_k2_6_w4a8_16p_in64k_out1k_100ms.py
+            test_type: 'perf'
           - name: kimi_k2_6_w4a8_16p_in64k_out1k_100ms_aime25
             node_size: 2
-            test_case: test/registered/ascend/performance/kimi_k2_6/test_npu_kimi_k2_6_w4a8_16p_in64k_out1k_100ms_aime25.py
+            test_case: test/registered/npu/accuracy/kimi_k2_6/test_npu_kimi_k2_6_w4a8_16p_in64k_out1k_100ms_aime25.py
-            test_type: 'perf'
     uses: ./.github/workflows/nightly-test-npu-e2e-multi-node.yml
     with:
       runner: linux-amd64-cpu-8

.github/workflows/pr-test-npu.yml

@@ -59,7 +59,7 @@ jobs:
               - "python/sglang/!(multimodal_gen)/**/!(*.md)"
               - "python/pyproject_npu.toml"
               - "scripts/ci/npu/npu_ci_install_dependency.sh"
-              - "test/registered/ascend/**"
+              - "test/registered/npu/**"
               - "test/registered/unit/npu/**"
               - ".github/workflows/pr-test-npu.yml"
             multimodal_gen:
@@ -461,7 +461,78 @@ jobs:
           # qwen3_6_27b performance tests
           - name: qwen3_6_27b_w8a8_1p_in64k_out1k_50ms
             runner: linux-aarch64-a3-2
-            test_case: test/registered/ascend/performance/qwen3_6_27b/test_npu_qwen3_6_27b_w8a8_1p_in64k_out1k_50ms.py
+            test_case: test/registered/npu/performance/qwen3_6_27b/test_npu_qwen3_6_27b_w8a8_1p_in64k_out1k_50ms.py
+            test_type: 'perf'
+
+          - name: qwen3_6_27b_1p_in1024x1024_30_out1024_50ms
+            runner: linux-aarch64-a3-2
+            test_case: test/registered/npu/performance/qwen3_6_27b/test_npu_qwen3_6_27b_1p_in1024x1024_30_out1024_50ms.py
+            test_type: 'perf'
+
+          # qwen3_8b performance tests
+          - name: qwen3_8b_w8a8_1p_in3k5_out1k5_50ms
+            runner: linux-aarch64-a3-2
+            test_case: test/registered/npu/performance/qwen3-8b/test_npu_qwen3_8b_w8a8_1p_in3k5_out1k5_50ms.py
+            test_type: 'perf'
+
+          # qwen3_30b_a3b performance tests
+          - name: qwen3_30b_w8a8_1p_in3k5_out1k5_50ms
+            runner: linux-aarch64-a3-2
+            test_case: test/registered/npu/performance/qwen3_30b_a3b/test_npu_qwen3_30b_w8a8_1p_in3k5_out1k5_50ms.py
+            test_type: 'perf'
+
+          # qwen3_6_35b_a3b performance tests
+          - name: qwen3_6_35b_a3b_1p_in64k_out1k_prefix90_50ms
+            runner: linux-aarch64-a3-2
+            test_case: test/registered/npu/performance/qwen3_6_35b_a3b/test_npu_qwen3_6_35b_a3b_1p_in64k_out1k_prefix90_50ms.py
+            test_type: 'perf'
+
+          # qwen3_vl_8b_thinking accuracy tests
+          - name: qwen3_vl_8b_thinking_1p_mmmu
+            runner: linux-aarch64-a3-2
+            test_case: test/registered/npu/accuracy/qwen3_vl_8b_thinking/test_npu_qwen3_vl_8b_thinking_1p_mmmu.py
+            test_type: 'accuracy'
+
+          # qwen3_32b performance tests
+          - name: qwen3_32b_w8a8_2p_in3k5_out1k5_50ms
+            runner: linux-aarch64-a3-4
+            test_case: test/registered/npu/performance/qwen3_32b/test_npu_qwen3_32b_w8a8_2p_in3k5_out1k5_50ms.py
+            test_type: 'perf'
+
+          # qwen3_next_80b_a3b performance tests
+          - name: qwen3_next_80b_w8a8_2p_in6k_out1k5_bs16
+            runner: linux-aarch64-a3-4
+            test_case: test/registered/npu/performance/qwen3_next_80b_a3b_instruct/test_npu_qwen3_next_80b_w8a8_2p_in6k_out1k5_bs16.py
+            test_type: 'perf'
+
+          # minimax_m2_5 performance tests
+          - name: minimax_m2_5_w8a8_4p_in64k_out1k_prefix90_50ms
+            runner: linux-aarch64-a3-8
+            test_case: test/registered/npu/performance/minimax_m2_5/test_npu_minimax_m2_5_w8a8_4p_in64k_out1k_prefix90_50ms.py
+            test_type: 'perf'
+
+          # deepseek_v4_flash performance tests
+          - name: deepseek_v4_flash_w8a8_8p_in8k_out1k_50ms
+            runner: linux-aarch64-a3-16
+            test_case: test/registered/npu/performance/deepseek_v4_flash/test_npu_deepseek_v4_flash_w8a8_8p_in8k_out1k_50ms.py
+            test_type: 'perf'
+
+          # kimi_k2_6 performance tests
+          - name: kimi_k2_6_w4a8_8p_in3k5_out1k5_20ms
+            runner: linux-aarch64-a3-16
+            test_case: test/registered/npu/performance/kimi_k2_6/test_npu_kimi_k2_6_w4a8_8p_in3k5_out1k5_20ms.py
+            test_type: 'perf'
+
+          # qwen3_235b performance tests
+          - name: qwen3_235b_w8a8_8p_in3k5_out1k5_50ms
+            runner: linux-aarch64-a3-16
+            test_case: test/registered/npu/performance/qwen3_235b_a22b/test_npu_qwen3_235b_w8a8_8p_in3k5_out1k5_50ms.py
+            test_type: 'perf'
+
+          # qwen3_5_397b performance tests
+          - name: qwen3_5_397b_w4a8_8p_in3k5_out1k5_50ms
+            runner: linux-aarch64-a3-16
+            test_case: test/registered/npu/performance/qwen3_5_397b/test_npu_qwen3_5_397b_w4a8_8p_in3k5_out1k5_50ms.py
             test_type: 'perf'
           # NPU accuracy tests
           - name: glm4_7_flash_1p_gsm8k

docs_new/docs/hardware-platforms/ascend-npus/development/contribution_guide.mdx

@@ -42,7 +42,7 @@ pre-commit run --all-files
 ## Run and add tests
 
 All NPU tests are end-to-end (E2E) and require launching a server with real model weights.
-Tests live under [`test/registered/ascend/`](https://github.com/sgl-project/sglang/tree/main/test/registered/ascend), organized by model type and functionality:
+Tests live under [`test/registered/npu/`](https://github.com/sgl-project/sglang/tree/main/test/registered/npu), organized by model type and functionality:
 
 ```
 ascend/
@@ -58,9 +58,9 @@ ascend/
 
 ### Adding a test
 
-See [`test_npu_sampling_backend.py`](https://github.com/sgl-project/sglang/tree/main/test/registered/ascend/basic_function/backends/test_npu_sampling_backend.py) for a complete example. Key steps:
+See [`test_npu_sampling_backend.py`](https://github.com/sgl-project/sglang/tree/main/test/registered/npu/basic_function/backends/test_npu_sampling_backend.py) for a complete example. Key steps:
 
-1. Place your test file in the appropriate directory under `test/registered/ascend/`.
+1. Place your test file in the appropriate directory under `test/registered/npu/`.
 2. Extend `CustomTestCase` (from `sglang.test.test_utils`) for CI retry support.
 3. Launch server with `popen_launch_server()` in `setUpClass` and clean up with `kill_process_tree()` in `tearDownClass`.
 4. Register your test with `register_npu_ci()`:
@@ -73,7 +73,7 @@ See [`test_npu_sampling_backend.py`](https://github.com/sgl-project/sglang/tree/
 ### Running tests locally
 
 ```bash
-pytest test/registered/ascend/llm_models/test_npu_qwen3_0_6b.py -v
+pytest test/registered/npu/llm_models/test_npu_qwen3_0_6b.py -v
 ```
 
 For detailed instructions, refer to [test/README.md](https://github.com/sgl-project/sglang/tree/main/test/README.md).

docs_new/docs/hardware-platforms/ascend-npus/development/support_new_models.mdx

@@ -71,7 +71,7 @@ Please note all your testing and benchmarking results in PR description.
 - **(Optional) Other evals**: If you ran other evals, please note the results in PR description.
 
 <Tip>
-For NPU-adapted models: add the corresponding test under `test/registered/ascend/` and verify correctness on Ascend NPU
+For NPU-adapted models: add the corresponding test under `test/registered/npu/` and verify correctness on Ascend NPU
 hardware; run benchmarks on the NPU device and report performance metrics (TTFT, throughput), comparing against SGLang
 GPU results as the primary baseline. Fall back to HF Transformer comparison when no GPU adaptation is available.
 </Tip>

python/sglang/test/ascend/test_ascend_utils.py

@@ -53,7 +53,7 @@ BAICHUAN2_13B_CHAT_WEIGHTS_PATH = os.path.join(
 C4AI_COMMAND_R_V01_WEIGHTS_PATH = os.path.join(
     MODEL_WEIGHTS_DIR, "CohereForAI/c4ai-command-r-v01"
 )
-C4AI_COMMAND_R_V01_CHAT_TEMPLATE_PATH = "/__w/sglang/sglang/test/registered/ascend/llm_models/tool_chat_template_c4ai_command_r_v01.jinja"
+C4AI_COMMAND_R_V01_CHAT_TEMPLATE_PATH = "/__w/sglang/sglang/test/registered/npu/llm_models/tool_chat_template_c4ai_command_r_v01.jinja"
 CHATGLM2_6B_WEIGHTS_PATH = os.path.join(MODEL_WEIGHTS_DIR, "ZhipuAI/chatglm2-6b")
 DBRX_INSTRUCT_WEIGHTS_PATH = os.path.join(
     MODEL_WEIGHTS_DIR, "AI-ModelScope/dbrx-instruct"
@@ -378,10 +378,10 @@ INVOICE_WITH_BARCODE_LOGO_IMAGES_PATH = os.path.join(
 # fmt: on
 
 # Other
-DEEPSEEK_CODER_JSON_PATH = "/__w/sglang/sglang/test/registered/ascend/basic_function/parameter/deepseek_coder.json"
+DEEPSEEK_CODER_JSON_PATH = "/__w/sglang/sglang/test/registered/npu/basic_function/parameter/deepseek_coder.json"
 FR_SPEC_TOKEN_MAP_PATH = "/root/.cache/sglang/FR-Spec/freq_32768.pt"
 CONFIG_YAML_PATH = (
-    "/__w/sglang/sglang/test/registered/ascend/basic_function/config/config.yaml"
+    "/__w/sglang/sglang/test/registered/npu/basic_function/config/config.yaml"
 )
 
 

test/registered/README.md

@@ -18,6 +18,6 @@ Tests under this directory are auto-discovered by `run_suite.py` via CI registra
 | Model inference correctness | `models/`, `4-gpu-models/`, `8-gpu-models/` | GPU |
 | Feature-specific (OpenAI API, LoRA, speculative, distributed, VLM, etc.) | `openai_server/`, `lora/`, `spec/`, `distributed/`, ... | GPU |
 | Benchmarks (performance, accuracy, stress) | `benchmark/` | GPU |
-| Platform-specific | `amd/`, `ascend/` | Vendor GPU |
+| Platform-specific | `amd/`, `npu/` | Vendor GPU |
 
 See [`unit/README.md`](unit/README.md) for unit test conventions.

test/registered/npu/accuracy/glm5_1/test_npu_glm5_1_w4a8_1p1d_32p_in64k_out1k_50ms_aime26.py

@@ -5,10 +5,7 @@ from sglang.test.ascend.e2e.test_npu_accuracy_utils import (
 )
 from sglang.test.ascend.e2e.test_npu_multi_node_utils import NIC_NAME
 from sglang.test.ascend.e2e.test_npu_performance_utils import (
-    AISBENCHMARK_DATASET_DEFAULT,
-    BENCHMARK_TOOL_DEFAULT,
     GLM_5_1_W4A8_MODEL_PATH,
-    TestNpuPerfMultiNodePdSepTestCaseBase,
 )
 from sglang.test.ci.ci_register import register_npu_ci
 
@@ -16,7 +13,7 @@ register_npu_ci(
     est_time=3600,
     suite="",
     nightly=True,
-    disabled="performance testcase",
+    disabled="accuracy testcase",
 )
 
 GLM_5_1_PD_SEP_PREFILL_ENVS = {
@@ -181,26 +178,5 @@ class TestNPUGLM5_1_W4A8_PD_SEP_AIME2026(TestNpuAccuracyMultiNodePdSepTestCaseBa
         self.run_accuracy()
 
 
-class TestNPUGLM5_1_W4A8_PD_SEP_In3k5_Out1k5(TestNpuPerfMultiNodePdSepTestCaseBase):
-    """Test NPU performance for GLM-5.1-w4a8 PD separation 4 nodes in3k5 out1k5"""
-
-    model_config = GLM_5_1_PD_SEP_MODEL_CONFIG
-    benchmark_tool = BENCHMARK_TOOL_DEFAULT
-    dataset_type = AISBENCHMARK_DATASET_DEFAULT
-    dataset_name = "random"
-    max_concurrency = 1
-    num_prompts = 1
-    input_len = 65536
-    output_len = 1024
-    random_range_ratio = 1
-    seed = 1
-    tpot = 50
-    output_token_throughput = 160
-
-    def test_npu_glm5_1_w4a8_pd_sep_in3k5_out1k5(self):
-        """Run NPU performance test for GLM-5.1-w4a8 PD separation"""
-        self.run_throughput()
-
-
 if __name__ == "__main__":
     unittest.main()

test/registered/npu/accuracy/kimi_k2_6/test_npu_kimi_k2_6_w4a8_16p_in64k_out1k_100ms_aime25.py

@@ -5,11 +5,8 @@ from sglang.test.ascend.e2e.test_npu_accuracy_utils import (
 )
 from sglang.test.ascend.e2e.test_npu_multi_node_utils import NIC_NAME
 from sglang.test.ascend.e2e.test_npu_performance_utils import (
-    AISBENCHMARK_DATASET_DEFAULT,
-    BENCHMARK_TOOL_DEFAULT,
     KIMI_K2_6_EAGLE3_MODEL_PATH,
     KIMI_K2_6_W4A8_MODEL_PATH,
-    TestNpuPerfMultiNodePdMixTestCaseBase,
 )
 from sglang.test.ci.ci_register import register_npu_ci
 
@@ -17,7 +14,7 @@ register_npu_ci(
     est_time=1800,
     suite="nightly-8-npu-a3",
     nightly=True,
-    disabled="Currently it is executed by the npu performance workflow.",
+    disabled="accuracy testcase",
 )
 
 ENVS = {
@@ -107,23 +104,5 @@ class TestNPUKimiK2_6_W4A8_16P_AIME2025(TestNpuAccuracyMultiNodePdMixTestCaseBas
         self.run_accuracy()
 
 
-class TestNPUKimiK2_6_W4A8_16P_In64k_Out1k_100ms(TestNpuPerfMultiNodePdMixTestCaseBase):
-    benchmark_tool = BENCHMARK_TOOL_DEFAULT
-    dataset_type = AISBENCHMARK_DATASET_DEFAULT
-    model_config = MODEL_CONFIG
-    dataset_name = "random"
-    max_concurrency = 32
-    num_prompts = 32
-    input_len = 64000
-    output_len = 1000
-    random_range_ratio = 1
-    seed = 1
-    tpot = 100
-    output_token_throughput = 160
-
-    def test_npu_kimi_k2_6_w4a8_16p_in64k_out1k_100ms(self):
-        self.run_throughput()
-
-
 if __name__ == "__main__":
     unittest.main()

test/registered/npu/accuracy/minimax_m2_5/test_npu_minimax_m2_5_w8a8_4p_in64k_out1k_prefix90_50ms_gpqa.py

@@ -0,0 +1,109 @@
+import os
+import unittest
+
+from sglang.test.ascend.e2e.test_npu_accuracy_utils import (
+    TestNpuAccuracyTestCaseBase,
+)
+from sglang.test.ascend.e2e.test_npu_performance_utils import (
+    MINIMAX_M2_5_EAGLE3_MODEL_PATH,
+    MINIMAX_M2_5_W8A8_MODEL_PATH,
+)
+from sglang.test.ci.ci_register import register_npu_ci
+
+register_npu_ci(
+    est_time=3600,
+    suite="",
+    nightly=True,
+    disabled="accuracy testcase",
+)
+
+MINIMAX_M2_5_W8A8_4P_IN64K_OUT1K_PREFIX90_ENVS = {
+    "PYTORCH_NPU_ALLOC_CONF": "expandable_segments:True",
+    "STREAMS_PER_DEVICE": "32",
+    "HCCL_SOCKET_IFNAME": "lo",
+    "GLOO_SOCKET_IFNAME": "lo",
+    "TASK_QUEUE_ENABLE": "1",
+    "ASCEND_USE_FIA": "1",
+    "SGLANG_SET_CPU_AFFINITY": "1",
+    "SGLANG_ENABLE_OVERLAP_PLAN_STREAM": "1",
+    "SGLANG_NPU_FUSED_MOE_MODE": "2",
+    "SGLANG_DEEPEP_NUM_MAX_DISPATCH_TOKENS_PER_RANK": "140000",
+    "DEEP_NORMAL_MODE_USE_INT8_QUANT": "1",
+    "DEEPEP_HCCL_BUFFSIZE": "1024",
+    "SGLANG_EXTERNAL_MODEL_PACKAGE": "custom_eagle3",
+    "PYTHONPATH": f"{MINIMAX_M2_5_EAGLE3_MODEL_PATH}:{os.environ.get('PYTHONPATH', '')}",
+}
+
+MINIMAX_M2_5_W8A8_4P_IN64K_OUT1K_PREFIX90_OTHER_ARGS = [
+    "--tp-size",
+    8,
+    "--mem-fraction-static",
+    0.63,
+    "--max-running-requests",
+    26,
+    "--reasoning-parser",
+    "minimax-append-think",
+    "--tool-call-parser",
+    "minimax-m2",
+    "--enable-prefill-delayer",
+    "--prefill-max-requests",
+    10,
+    "--chunked-prefill-size",
+    67072,
+    "--max-prefill-token",
+    67000,
+    "--cuda-graph-bs",
+    2,
+    4,
+    8,
+    12,
+    16,
+    18,
+    20,
+    22,
+    24,
+    26,
+    "--moe-a2a-backend",
+    "ascend_fuseep",
+    "--deepep-mode",
+    "auto",
+    "--quantization",
+    "modelslim",
+    "--speculative-algorithm",
+    "EAGLE3",
+    "--speculative-draft-model-path",
+    MINIMAX_M2_5_EAGLE3_MODEL_PATH,
+    "--speculative-num-steps",
+    3,
+    "--speculative-eagle-topk",
+    1,
+    "--speculative-num-draft-tokens",
+    4,
+    "--speculative-draft-model-quantization",
+    "unquant",
+    "--dtype",
+    "bfloat16",
+    "--trust-remote-code",
+    "--reasoning-parser",
+    "minimax-append-think",
+    "--tool-call-parser",
+    "minimax-m2",
+]
+
+
+class TestNPUMiniMaxM2_5_W8A8_4P_Gpqa(TestNpuAccuracyTestCaseBase):
+    model = MINIMAX_M2_5_W8A8_MODEL_PATH
+    other_args = MINIMAX_M2_5_W8A8_4P_IN64K_OUT1K_PREFIX90_OTHER_ARGS
+    envs = MINIMAX_M2_5_W8A8_4P_IN64K_OUT1K_PREFIX90_ENVS
+    accuracy = 0.852
+    datasets = ["gpqa_diamond"]
+    few_shot_num = 0
+    generation_config = {"max_tokens": 65536, "temperature": 1.0}
+    eval_batch_size = 64
+
+    def test_accuracy(self):
+        self.run_accuracy()
+
+
+if __name__ == "__main__":
+    unittest.main()

test/registered/npu/accuracy/minimax_m2_5/test_npu_minimax_m2_5_w8a8_8p_in3k5_out1k5_50ms_gpqa.py

@@ -0,0 +1,107 @@
+import os
+import unittest
+
+from sglang.test.ascend.e2e.test_npu_accuracy_utils import (
+    TestNpuAccuracyTestCaseBase,
+)
+from sglang.test.ascend.e2e.test_npu_performance_utils import (
+    MINIMAX_M2_5_EAGLE3_MODEL_PATH,
+    MINIMAX_M2_5_W8A8_MODEL_PATH,
+)
+from sglang.test.ci.ci_register import register_npu_ci
+
+register_npu_ci(
+    est_time=3600,
+    suite="full-16-npu-a3",
+    nightly=True,
+    disabled="accuracy testcase",
+)
+
+MINIMAX_M2_5_HIGH_THROUGHPUT_ENVS = {
+    "PYTORCH_NPU_ALLOC_CONF": "expandable_segments:True",
+    "STREAMS_PER_DEVICE": "32",
+    "HCCL_SOCKET_IFNAME": "lo",
+    "GLOO_SOCKET_IFNAME": "lo",
+    "TASK_QUEUE_ENABLE": "1",
+    "DEEPEP_HCCL_BUFFSIZE": "1024",
+    "ASCEND_USE_FIA": "1",
+    "SGLANG_SET_CPU_AFFINITY": "1",
+    "SGLANG_ENABLE_OVERLAP_PLAN_STREAM": "1",
+    "SGLANG_DEEPEP_NUM_MAX_DISPATCH_TOKENS_PER_RANK": "204800",
+    "PYTHONPATH": f"{MINIMAX_M2_5_EAGLE3_MODEL_PATH}:{os.environ.get('PYTHONPATH', '')}",
+    "SGLANG_EXTERNAL_MODEL_PACKAGE": "custom_eagle3",
+}
+
+MINIMAX_M2_5_HIGH_THROUGHPUT_OTHER_ARGS = [
+    "--tp-size",
+    16,
+    "--enable-dp-attention",
+    "--dp-size",
+    16,
+    "--mem-fraction-static",
+    0.75,
+    "--max-running-requests",
+    320,
+    "--disable-radix-cache",
+    "--reasoning-parser",
+    "minimax-append-think",
+    "--tool-call-parser",
+    "minimax-m2",
+    "--prefill-delayer-max-delay-passes",
+    500,
+    "--enable-prefill-delayer",
+    "--chunked-prefill-size",
+    196608,
+    "--max-prefill-token",
+    8192,
+    "--cuda-graph-bs",
+    1,
+    2,
+    4,
+    8,
+    12,
+    16,
+    20,
+    "--moe-a2a-backend",
+    "ascend_fuseep",
+    "--fuseep-mode",
+    2,
+    "--quantization",
+    "modelslim",
+    "--speculative-algorithm",
+    "EAGLE3",
+    "--speculative-draft-model-path",
+    MINIMAX_M2_5_EAGLE3_MODEL_PATH,
+    "--speculative-num-steps",
+    3,
+    "--speculative-eagle-topk",
+    1,
+    "--speculative-num-draft-tokens",
+    4,
+    "--speculative-draft-model-quantization",
+    "unquant",
+    "--dtype",
+    "bfloat16",
+    "--reasoning-parser",
+    "minimax-append-think",
+    "--tool-call-parser",
+    "minimax-m2",
+]
+
+
+class TestNPUMiniMaxM2_5_W8A8_8P_In3k5_Out1k5_GPQA(TestNpuAccuracyTestCaseBase):
+    model = MINIMAX_M2_5_W8A8_MODEL_PATH
+    envs = MINIMAX_M2_5_HIGH_THROUGHPUT_ENVS
+    other_args = MINIMAX_M2_5_HIGH_THROUGHPUT_OTHER_ARGS
+    accuracy = 0.852
+    datasets = ["gpqa_diamond"]
+    few_shot_num = 0
+    generation_config = {"max_tokens": 65536, "temperature": 1.0}
+    eval_batch_size = 64
+
+    def test_accuracy(self):
+        self.run_accuracy()
+
+
+if __name__ == "__main__":
+    unittest.main()

test/registered/npu/accuracy/qwen3-8b/test_npu_qwen3_8b_w8a8_1p_in3k5_out1k5_50ms_gpqa.py

@@ -4,11 +4,8 @@ from sglang.test.ascend.e2e.test_npu_accuracy_utils import (
     TestNpuAccuracyTestCaseBase,
 )
 from sglang.test.ascend.e2e.test_npu_performance_utils import (
-    AISBENCHMARK_DATASET_DEFAULT,
-    BENCHMARK_TOOL_DEFAULT,
     QWEN3_8B_EAGLE_MODEL_PATH,
     QWEN3_8B_W8A8_MODEL_PATH,
-    TestNpuPerformanceTestCaseBase,
 )
 from sglang.test.ci.ci_register import register_npu_ci
 
@@ -16,7 +13,7 @@ register_npu_ci(
     est_time=3600,
     suite="",
     nightly=True,
-    disabled="performance testcase",
+    disabled="accuracy testcase",
 )
 
 QWEN3_8B_ENVS = {
@@ -88,26 +85,6 @@ QWEN3_8B_OTHER_ARGS = [
 ]
 
 
-class TestQwen8B(TestNpuPerformanceTestCaseBase):
-    benchmark_tool = BENCHMARK_TOOL_DEFAULT
-    dataset_type = AISBENCHMARK_DATASET_DEFAULT
-    model = QWEN3_8B_W8A8_MODEL_PATH
-    other_args = QWEN3_8B_OTHER_ARGS
-    envs = QWEN3_8B_ENVS
-    dataset_name = "random"
-    max_concurrency = 64
-    num_prompts = 256
-    input_len = 3500
-    output_len = 1500
-    random_range_ratio = 1
-    seed = 1
-    tpot = 37
-    output_token_throughput = 1586
-
-    def test_qwen3_8b(self):
-        self.run_throughput()
-
-
 class TestQwen8B_gpqa(TestNpuAccuracyTestCaseBase):
     model = QWEN3_8B_W8A8_MODEL_PATH
     envs = QWEN3_8B_ENVS

test/registered/npu/accuracy/qwen3-8b/test_npu_qwen3_8b_w8a8_1p_in6k_out1k5_bs16_gpqa.py

@@ -6,7 +6,6 @@ from sglang.test.ascend.e2e.test_npu_accuracy_utils import (
 from sglang.test.ascend.e2e.test_npu_performance_utils import (
     QWEN3_8B_EAGLE_MODEL_PATH,
     QWEN3_8B_W8A8_MODEL_PATH,
-    TestNpuPerformanceTestCaseBase,
 )
 from sglang.test.ci.ci_register import register_npu_ci
 
@@ -14,7 +13,7 @@ register_npu_ci(
     est_time=3600,
     suite="",
     nightly=True,
-    disabled="performance testcase",
+    disabled="accuracy testcase",
 )
 
 QWEN3_8B_ENVS = {
@@ -75,24 +74,6 @@ QWEN3_8B_OTHER_ARGS = [
 ]
 
 
-class TestQwen8B(TestNpuPerformanceTestCaseBase):
-    max_attempts = 5
-    model = QWEN3_8B_W8A8_MODEL_PATH
-    other_args = QWEN3_8B_OTHER_ARGS
-    envs = QWEN3_8B_ENVS
-    dataset_name = "random"
-    max_concurrency = 16
-    num_prompts = 16
-    input_len = 6144
-    output_len = 1500
-    random_range_ratio = 1
-    tpot = 11.79
-    output_token_throughput = 1040.96
-
-    def test_qwen3_8b(self):
-        self.run_throughput()
-
-
 class TestQwen8B_gpqa(TestNpuAccuracyTestCaseBase):
     model = QWEN3_8B_W8A8_MODEL_PATH
     envs = QWEN3_8B_ENVS

test/registered/npu/accuracy/qwen3_30b_a3b/test_npu_qwen3_30b_w8a8_1p_in3k5_out1k5_50ms_aime25.py

@@ -4,11 +4,8 @@ from sglang.test.ascend.e2e.test_npu_accuracy_utils import (
     TestNpuAccuracyTestCaseBase,
 )
 from sglang.test.ascend.e2e.test_npu_performance_utils import (
-    AISBENCHMARK_DATASET_DEFAULT,
-    BENCHMARK_TOOL_DEFAULT,
     QWEN3_30B_A3B_W8A8_VLLM_MODEL_PATH,
     QWEN3_A3B_EAGLE_MODEL_PATH,
-    TestNpuPerformanceTestCaseBase,
 )
 from sglang.test.ci.ci_register import register_npu_ci
 
@@ -16,7 +13,7 @@ register_npu_ci(
     est_time=3600,
     suite="",
     nightly=True,
-    disabled="performance testcase",
+    disabled="accuracy testcase",
 )
 
 QWEN3_30B_A3B_ENVS = {
@@ -93,26 +90,6 @@ QWEN3_30B_A3B_OTHER_ARGS = [
 ]
 
 
-class TestQwen30B(TestNpuPerformanceTestCaseBase):
-    benchmark_tool = BENCHMARK_TOOL_DEFAULT
-    dataset_type = AISBENCHMARK_DATASET_DEFAULT
-    model = QWEN3_30B_A3B_W8A8_VLLM_MODEL_PATH
-    other_args = QWEN3_30B_A3B_OTHER_ARGS
-    envs = QWEN3_30B_A3B_ENVS
-    dataset_name = "random"
-    max_concurrency = 160
-    num_prompts = int(max_concurrency) * 4
-    input_len = 3500
-    output_len = 1500
-    random_range_ratio = 1
-    seed = 1
-    tpot = 50
-    output_token_throughput = 3200
-
-    def test_qwen3_30b(self):
-        self.run_throughput()
-
-
 class TestQwen30B_A3B_aime25(TestNpuAccuracyTestCaseBase):
     model = QWEN3_30B_A3B_W8A8_VLLM_MODEL_PATH
     envs = QWEN3_30B_A3B_ENVS

test/registered/npu/accuracy/qwen3_32b/test_npu_qwen3_32b_w8a8_2p_in3k5_out1k5_50ms_gpqa.py

@@ -4,11 +4,8 @@ from sglang.test.ascend.e2e.test_npu_accuracy_utils import (
     TestNpuAccuracyTestCaseBase,
 )
 from sglang.test.ascend.e2e.test_npu_performance_utils import (
-    AISBENCHMARK_DATASET_DEFAULT,
-    BENCHMARK_TOOL_DEFAULT,
     QWEN3_32B_EAGLE_MODEL_PATH,
     QWEN3_32B_W8A8_MODEL_PATH,
-    TestNpuPerformanceTestCaseBase,
 )
 from sglang.test.ci.ci_register import register_npu_ci
 
@@ -16,7 +13,7 @@ register_npu_ci(
     est_time=3600,
     suite="",
     nightly=True,
-    disabled="performance testcase",
+    disabled="accuracy testcase",
 )
 
 QWEN3_32B_ENVS = {
@@ -90,27 +87,7 @@ QWEN3_32B_OTHER_ARGS = [
 ]
 
 
-class TestQwen32B(TestNpuPerformanceTestCaseBase):
+class TestQwen32B_gpqa(TestNpuAccuracyTestCaseBase):
-    benchmark_tool = BENCHMARK_TOOL_DEFAULT
-    dataset_type = AISBENCHMARK_DATASET_DEFAULT
-    model = QWEN3_32B_W8A8_MODEL_PATH
-    other_args = QWEN3_32B_OTHER_ARGS
-    envs = QWEN3_32B_ENVS
-    dataset_name = "random"
-    max_concurrency = 100
-    num_prompts = 400
-    input_len = 3584
-    output_len = 1536
-    random_range_ratio = 1
-    seed = 1
-    tpot = 50
-    output_token_throughput = 1600
-
-    def test_qwen3_32b(self):
-        self.run_throughput()
-
-
-class TestQwen32B_mmlupro(TestNpuAccuracyTestCaseBase):
     model = QWEN3_32B_W8A8_MODEL_PATH
     envs = QWEN3_32B_ENVS
     other_args = QWEN3_32B_OTHER_ARGS

test/registered/npu/accuracy/qwen3_32b/test_npu_qwen3_32b_w8a8_2p_in3k5_out1k5_50ms_gpqa_a2.py

@@ -0,0 +1,108 @@
+import unittest
+
+from sglang.test.ascend.e2e.test_npu_accuracy_utils import (
+    TestNpuAccuracyTestCaseBase,
+)
+from sglang.test.ascend.e2e.test_npu_performance_utils import (
+    QWEN3_32B_EAGLE_MODEL_PATH,
+    QWEN3_32B_W8A8_MODEL_PATH,
+)
+from sglang.test.ci.ci_register import register_npu_ci
+
+register_npu_ci(
+    est_time=3600,
+    suite="",
+    nightly=True,
+    disabled="accuracy testcase",
+)
+
+QWEN3_32B_ENVS = {
+    "SGLANG_DISAGGREGATION_BOOTSTRAP_TIMEOUT": "600",
+    "PYTORCH_NPU_ALLOC_CONF": "expandable_segments:True",
+    "HCCL_SOCKET_IFNAME": "lo",
+    "GLOO_SOCKET_IFNAME": "lo",
+    "HCCL_OP_EXPANSION_MODE": "AIV",
+    "SGLANG_ENABLE_OVERLAP_PLAN_STREAM": "1",
+    "SGLANG_SCHEDULER_DECREASE_PREFILL_IDLE": "1",
+    "SGLANG_PREFILL_DELAYER_MAX_DELAY_PASSES": "100",
+    "SGLANG_NPU_USE_DEEPGEMM": "1",
+}
+
+QWEN3_32B_OTHER_ARGS = [
+    "--trust-remote-code",
+    "--nnodes",
+    "1",
+    "--node-rank",
+    "0",
+    "--attention-backend",
+    "ascend",
+    "--device",
+    "npu",
+    "--quantization",
+    "modelslim",
+    "--max-running-requests",
+    101,
+    "--disable-radix-cache",
+    "--speculative-draft-model-quantization",
+    "unquant",
+    "--chunked-prefill-size",
+    -1,
+    "--max-prefill-tokens",
+    35000,
+    "--speculative-algorithm",
+    "EAGLE3",
+    "--speculative-draft-model-path",
+    QWEN3_32B_EAGLE_MODEL_PATH,
+    "--speculative-num-steps",
+    3,
+    "--speculative-eagle-topk",
+    1,
+    "--speculative-num-draft-tokens",
+    4,
+    "--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",
+    "--reasoning-parser",
+    "qwen3",
+    "--tool-call-parser",
+    "qwen",
+]
+
+
+class TestQwen32B_GPQA(TestNpuAccuracyTestCaseBase):
+    """Test NPU accuracy for Qwen3-32B-W8A8 on qpqa"""
+
+    model = QWEN3_32B_W8A8_MODEL_PATH
+    other_args = QWEN3_32B_OTHER_ARGS
+    envs = QWEN3_32B_ENVS
+    accuracy = 0.4949
+    datasets = ["gpqa_diamond"]
+    few_shot_num = 0
+    eval_batch_size = 64
+    generation_config = {"max_tokens": 40000, "temperature": 1.0}
+
+    def test_qwen3_32b_qpqa(self):
+        """Run NPU accuracy test for Qwen3-32B-W8A8 on qpqa"""
+        self.run_accuracy()
+
+
+if __name__ == "__main__":
+    unittest.main()

test/registered/npu/accuracy/qwen3_6_27b/test_npu_qwen3_6_27b_w8a8_1p_in3k5_out1k5_50ms_gpqa.py

@@ -0,0 +1,106 @@
+import unittest
+
+from sglang.test.ascend.e2e.test_npu_accuracy_utils import (
+    TestNpuAccuracyTestCaseBase,
+)
+from sglang.test.ascend.e2e.test_npu_performance_utils import (
+    QWEN3_6_27B_W8A8_MODEL_PATH,
+)
+from sglang.test.ci.ci_register import register_npu_ci
+
+register_npu_ci(
+    est_time=3600,
+    suite="full-2-npu-a3",
+    nightly=True,
+    disabled="accuracy testcase",
+)
+
+QWEN3_6_27B_3K5_1K5_ENVS = {
+    "PYTORCH_NPU_ALLOC_CONF": "expandable_segments:True",
+    "STREAMS_PER_DEVICE": "32",
+    "HCCL_SOCKET_IFNAME": "lo",
+    "GLOO_SOCKET_IFNAME": "lo",
+    "HCCL_OP_EXPANSION_MODE": "AIV",
+    "SGLANG_SET_CPU_AFFINITY": "1",
+    "SGLANG_ENABLE_OVERLAP_PLAN_STREAM": "0",
+    "SGLANG_SCHEDULER_DECREASE_PREFILL_IDLE": "1",
+    "SGLANG_PREFILL_DELAYER_MAX_DELAY_PASSES": "130",
+    "ASCEND_USE_FIA": "1",
+}
+
+QWEN3_6_27B_3K5_1K5_OTHER_ARGS = [
+    "--tp-size",
+    2,
+    "--nnodes",
+    1,
+    "--attention-backend",
+    "ascend",
+    "--device",
+    "npu",
+    "--chunked-prefill-size",
+    -1,
+    "--max-prefill-tokens",
+    60000,
+    "--disable-radix-cache",
+    "--trust-remote-code",
+    "--max-running-requests",
+    64,
+    "--max-mamba-cache-size",
+    74,
+    "--mem-fraction-static",
+    0.7,
+    "--cuda-graph-bs",
+    2,
+    8,
+    16,
+    32,
+    40,
+    45,
+    50,
+    54,
+    "--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,
+    "--reasoning-parser",
+    "qwen3",
+    "--tool-call-parser",
+    "qwen3_coder",
+]
+
+
+class TestNPUQwen3_6_27B_1P_In3k5_Out1k5_gpqa(TestNpuAccuracyTestCaseBase):
+    model = QWEN3_6_27B_W8A8_MODEL_PATH
+    envs = QWEN3_6_27B_3K5_1K5_ENVS
+    other_args = QWEN3_6_27B_3K5_1K5_OTHER_ARGS
+    accuracy = 0.878
+    datasets = ["gpqa_diamond"]
+    few_shot_num = 0
+    eval_batch_size = 8
+    generation_config = {
+        "max_tokens": 81920,
+        "temperature": 1.0,
+        "extra_body": {
+            "chat_template_kwargs": {"enable_thinking": True},
+        },
+    }
+
+    def test_accuracy(self):
+        self.run_accuracy()
+
+
+if __name__ == "__main__":
+    unittest.main()

test/registered/npu/accuracy/qwen3_6_35b_a3b/test_npu_qwen3_6_35b_a3b_1p_in64k_out1k_prefix90_50ms_aime26.py

@@ -0,0 +1,107 @@
+import unittest
+
+from sglang.test.ascend.e2e.test_npu_accuracy_utils import (
+    TestNpuAccuracyTestCaseBase,
+)
+from sglang.test.ascend.e2e.test_npu_performance_utils import (
+    QWEN3_6_35B_A3B_MODEL_PATH,
+)
+from sglang.test.ci.ci_register import register_npu_ci
+
+register_npu_ci(
+    est_time=3600,
+    suite="",
+    nightly=True,
+    disabled="accuracy testcase",
+)
+
+QWEN3_6_35B_A3B_64K_PREFIX_ENVS = {
+    "PYTORCH_NPU_ALLOC_CONF": "expandable_segments:True",
+    "STREAMS_PER_DEVICE": "32",
+    "DEEPEP_HCCL_BUFFSIZE": "300",
+    "HCCL_SOCKET_IFNAME": "lo",
+    "GLOO_SOCKET_IFNAME": "lo",
+    "HCCL_OP_EXPANSION_MODE": "AIV",
+    "SGLANG_SET_CPU_AFFINITY": "1",
+    "SGLANG_ENABLE_OVERLAP_PLAN_STREAM": "0",
+    "ASCEND_USE_FIA": "1",
+    "GDN_ATTN_BACKEND_TRITON": "1",
+}
+
+QWEN3_6_35B_A3B_64K_PREFIX_OTHER_ARGS = [
+    "--tp-size",
+    2,
+    "--nnodes",
+    1,
+    "--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",
+    200,
+    "--mem-fraction-static",
+    0.9,
+    "--cuda-graph-bs",
+    2,
+    8,
+    16,
+    24,
+    32,
+    36,
+    40,
+    "--enable-multimodal",
+    "--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,
+    "--reasoning-parser",
+    "qwen3",
+    "--tool-call-parser",
+    "qwen3_coder",
+]
+
+
+class TestNPUQwen3_6_35BA3B_1P_AIME2026(TestNpuAccuracyTestCaseBase):
+    """Test NPU accuracy for Qwen3.6-35B-A3B 1p on AIME2026"""
+
+    model = QWEN3_6_35B_A3B_MODEL_PATH
+    other_args = QWEN3_6_35B_A3B_64K_PREFIX_OTHER_ARGS
+    envs = QWEN3_6_35B_A3B_64K_PREFIX_ENVS
+    accuracy = 0.927
+    datasets = ["aime26"]
+    few_shot_num = 0
+    eval_batch_size = 64
+    generation_config = {
+        "max_tokens": 65536,
+        "temperature": 0.2,
+        "repetition_penalty": 1.08,
+    }
+
+    def test_npu_qwen3_6_35b_a3b_1p_aime2026(self):
+        """Run NPU accuracy test for Qwen3.6-35B-A3B on AIME2026"""
+        self.run_accuracy()
+
+
+if __name__ == "__main__":
+    unittest.main()

test/registered/npu/accuracy/qwen3_next_80b_a3b_instruct/test_npu_qwen3_next_80b_w8a8_2p_in6k_out1k5_bs16_aime25.py

@@ -6,7 +6,6 @@ from sglang.test.ascend.e2e.test_npu_accuracy_utils import (
 from sglang.test.ascend.e2e.test_npu_performance_utils import (
     QWEN3_NEXT_80B_A3B_MODEL_PATH,
     QWEN3_NEXT_80B_A3B_W8A8_MODEL_PATH,
-    TestNpuPerformanceTestCaseBase,
 )
 from sglang.test.ci.ci_register import register_npu_ci
 
@@ -14,7 +13,7 @@ register_npu_ci(
     est_time=3600,
     suite="",
     nightly=True,
-    disabled="performance testcase",
+    disabled="accuracy testcase",
 )
 
 QWEN3_NEXT_80B_A3B_ENVS = {
@@ -97,23 +96,6 @@ QWEN3_NEXT_80B_A3B_OTHER_ARGS = [
 ]
 
 
-class TestQwen3Next80BA3B(TestNpuPerformanceTestCaseBase):
-    max_attempts = 5
-    model = QWEN3_NEXT_80B_A3B_W8A8_MODEL_PATH
-    other_args = QWEN3_NEXT_80B_A3B_OTHER_ARGS
-    envs = QWEN3_NEXT_80B_A3B_ENVS
-    dataset_name = "random"
-    max_concurrency = 16
-    num_prompts = 16
-    input_len = 6144
-    output_len = 1500
-    random_range_ratio = 1
-    tpot = 15.62
-
-    def test_qwen3_next_80b_a3b(self):
-        self.run_throughput()
-
-
 class TestQwen3Next80BA3B_aime25(TestNpuAccuracyTestCaseBase):
     model = QWEN3_NEXT_80B_A3B_W8A8_MODEL_PATH
     envs = QWEN3_NEXT_80B_A3B_ENVS

test/registered/npu/accuracy/qwen3_vl_8b_thinking/test_npu_qwen3_vl_8b_thinking_1p_mmmu.py

@@ -1,3 +1,4 @@
+import os
 import unittest
 
 from sglang.test.ascend.e2e.test_npu_accuracy_utils import (
@@ -15,6 +16,8 @@ register_npu_ci(
     disabled="performance testcase",
 )
 
+_is_pr_pipeline = os.environ.get("GITHUB_EVENT_NAME") == "pull_request"
+
 ENVS = {
     "SGLANG_DISAGGREGATION_BOOTSTRAP_TIMEOUT": "600",
     "PYTORCH_NPU_ALLOC_CONF": "expandable_segments:True",
@@ -57,9 +60,10 @@ class TestQwen3(TestNpuAccuracyTestCaseBase):
     model = QWEN3_VL_8B_THINKING_MODEL_PATH
     envs = ENVS
     other_args = OTHER_ARGS
-    accuracy = 0.7011
+    accuracy = 0.64 if _is_pr_pipeline else 0.7011
     datasets = ["mmmu"]
     few_shot_num = 0
+    limit = 5 if _is_pr_pipeline else 100000
     generation_config = {"max_tokens": 65536}
     eval_batch_size = 64
 

test/registered/npu/basic_function/optimization_debug/test_npu_graph_tp1_bf16.py

@@ -12,8 +12,7 @@ from sglang.test.test_utils import (
     popen_launch_server,
 )
 
-register_npu_ci(est_time=400, suite="stage-b-test-1-npu-a2", nightly=False)
+register_npu_ci(est_time=400, suite="full-1-npu-a3", nightly=True)
-register_npu_ci(est_time=400, suite="nightly-1-npu-a3", nightly=True)
 
 TEST_MODEL_MATRIX = {
     "/root/.cache/modelscope/hub/models/Qwen/Qwen2.5-7B-Instruct": {

test/registered/npu/basic_function/optimization_debug/test_npu_graph_tp2_bf16.py

@@ -12,8 +12,7 @@ from sglang.test.test_utils import (
     popen_launch_server,
 )
 
-register_npu_ci(est_time=400, suite="stage-b-test-2-npu-a2", nightly=False)
+register_npu_ci(est_time=400, suite="full-2-npu-a3", nightly=True)
-register_npu_ci(est_time=400, suite="nightly-2-npu-a3", nightly=True)
 
 TEST_MODEL_MATRIX = {
     "/root/.cache/modelscope/hub/models/Qwen/Qwen2.5-7B-Instruct": {

test/registered/npu/basic_function/quant/test_npu_autoround_moe.py

@@ -10,7 +10,6 @@ from sglang.test.ascend.test_ascend_utils import (
 from sglang.test.ci.ci_register import register_npu_ci
 from sglang.test.few_shot_gsm8k import run_eval as run_eval_few_shot_gsm8k
 from sglang.test.test_utils import (
-    DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
     DEFAULT_URL_FOR_TEST,
     CustomTestCase,
     popen_launch_server,
@@ -53,7 +52,7 @@ class TestAscendAutoRoundMoE(CustomTestCase):
                 process = popen_launch_server(
                     model,
                     self.base_url,
-                    timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+                    timeout=3600,
                     other_args=[
                         *self.common_args,
                     ],