diff --git a/.github/workflows/nightly-test-npu.yml b/.github/workflows/nightly-test-npu.yml
index 6cde2e662..bff9ac74c 100644
--- a/.github/workflows/nightly-test-npu.yml
+++ b/.github/workflows/nightly-test-npu.yml
@@ -415,6 +415,11 @@ jobs:
             node_size: 2
             test_case: test/registered/npu/accuracy/glm5_2/test_npu_glm_5_2_w4a8_16p_gpqa.py
             test_type: 'accuracy'
+          # kimi_k3 accuracy tests
+          - name: kimi_k3_w4a8_32p_gpqa
+            node_size: 4
+            test_case: test/registered/npu/accuracy/kimi_k3/test_npu_kimi_k3_w4a8_32p_gpqa.py
+            test_type: 'accuracy'
     uses: ./.github/workflows/nightly-test-npu-e2e-multi-node.yml
     with:
       runner: linux-amd64-cpu-4
diff --git a/python/sglang/test/ascend/e2e/test_npu_performance_utils.py b/python/sglang/test/ascend/e2e/test_npu_performance_utils.py
index fc9736f23..8d8e5a51e 100644
--- a/python/sglang/test/ascend/e2e/test_npu_performance_utils.py
+++ b/python/sglang/test/ascend/e2e/test_npu_performance_utils.py
@@ -179,8 +179,8 @@ MINIMAX_M2_5_EAGLE3_MODEL_PATH = (
 QWEN3_5_397B_W8A8_MODEL_PATH = (
     "/root/.cache/modelscope/hub/models/Eco-Tech/Qwen3.5-397B-A17B-w8a8-mtp"
 )
-DEEPSEEK_V4_FLASH_W8A8_MTP_MODEL_PATH = (
-    "/root/.cache/modelscope/hub/models/Eco-Tech/DeepSeek-V4-Flash-w8a8-mtp"
+DEEPSEEK_V4_FLASH_0731_W8A8_MODEL_PATH = (
+    "/root/.cache/modelscope/hub/models/Eco-Tech/DeepSeek-V4-Flash-0731-w8a8"
 )
 QWEN3_5_397B_W4A8_MODEL_PATH = (
     "/root/.cache/modelscope/hub/models/Eco-Tech/Qwen3.5-397B-A17B-w4a8-mtp"
@@ -189,6 +189,8 @@ KIMI_K2_6_W4A8_MODEL_PATH = "/root/.cache/modelscope/hub/models/Eco-Tech/Kimi-K2
 KIMI_K2_6_EAGLE3_MODEL_PATH = (
     "/root/.cache/modelscope/hub/models/lightseekorg/kimi-k2.6-eagle3"
 )
+KIMI_K3_W4A8_MODEL_PATH = "/root/.cache/modelscope/hub/models/sgl-npu/Kimi-K3-W4A8"
+KIMI_K3_DSPARK_MODEL_PATH = "/root/.cache/modelscope/hub/models/RadixArk/Kimi-K3-DSpark"
 GLM_4_6V_FLASH_MODEL_PATH = "/root/.cache/modelscope/hub/models/ZhipuAI/GLM-4.6V-Flash"
 QWEN3_VL_8B_THINKING_MODEL_PATH = (
     "/root/.cache/modelscope/hub/models/Qwen/Qwen3-VL-8B-Thinking"
diff --git a/test/registered/npu/accuracy/deepseek_v4_flash/test_npu_deepseek_v4_flash_w8a8_8p_gpqa.py b/test/registered/npu/accuracy/deepseek_v4_flash/test_npu_deepseek_v4_flash_w8a8_8p_gpqa.py
new file mode 100644
index 000000000..a3bda90eb
--- /dev/null
+++ b/test/registered/npu/accuracy/deepseek_v4_flash/test_npu_deepseek_v4_flash_w8a8_8p_gpqa.py
@@ -0,0 +1,135 @@
+import unittest
+
+from sglang.test.ascend.e2e.test_npu_accuracy_utils import (
+    BENCHMARK_TOOL_DEFAULT,
+    TestNpuAccuracyTestCaseBase,
+)
+from sglang.test.ascend.e2e.test_npu_performance_utils import (
+    DEEPSEEK_V4_FLASH_0731_W8A8_MODEL_PATH,
+)
+from sglang.test.ci.ci_register import register_npu_ci
+
+register_npu_ci(
+    est_time=3600,
+    suite="nightly-acc-16-npu-a3",
+    nightly=True,
+)
+
+DEEPSEEK_V4_FLASH_W8A8_DSPARK_8P_ENVS = {
+    "PYTORCH_NPU_ALLOC_CONF": "expandable_segments:True",
+    "STREAMS_PER_DEVICE": "32",
+    "INF_NAN_MODE_FORCE_DISABLE": "1",
+    "SGLANG_SET_CPU_AFFINITY": "1",
+    "HCCL_SOCKET_IFNAME": "lo",
+    "GLOO_SOCKET_IFNAME": "lo",
+    "HCCL_OP_EXPANSION_MODE": "AIV",
+    # skip gpu branch
+    "SGLANG_OPT_FP8_WO_A_GEMM": "0",
+    "SGLANG_OPT_USE_OVERLAP_STORE_CACHE": "False",
+    "FORCE_DRAFT_MODEL_NON_QUANT": "1",
+    "SGLANG_DSV4_FP4_EXPERTS": "False",
+    "SGLANG_OPT_FUSE_WQA_WKV": "0",
+    "SGLANG_OPT_BF16_FP32_GEMM_ALGO": "torch",
+    "SGLANG_OPT_USE_FUSED_HASH_TOPK": "False",
+    "SGLANG_OPT_USE_TILELANG_MHC_PRE": "False",
+    "SGLANG_OPT_DEEPGEMM_HC_PRENORM": "False",
+    "SGLANG_OPT_USE_TILELANG_MHC_POST": "False",
+    # DSPARK
+    "SGLANG_RAGGED_VERIFY_MODE": "static",
+    "SGLANG_DSPARK_FAST_KERNEL": "0",
+    # deepep
+    "DEEP_NORMAL_MODE_USE_INT8_QUANT": "1",
+    "HCCL_BUFFSIZE": "1400",
+    "SGLANG_DEEPEP_NUM_MAX_DISPATCH_TOKENS_PER_RANK": "64",
+}
+
+DEEPSEEK_V4_FLASH_W8A8_DSPARK_8P_OTHER_ARGS = [
+    "--page-size",
+    128,
+    "--tp-size",
+    16,
+    "--trust-remote-code",
+    "--device",
+    "npu",
+    "--attention-backend",
+    "dsv4",
+    "--watchdog-timeout",
+    9000,
+    "--mem-fraction-static",
+    0.62,
+    "--prefill-max-requests",
+    32,
+    "--max-prefill-tokens",
+    131072,
+    "--chunked-prefill-size",
+    131072,
+    "--max-running-requests",
+    96,
+    "--dp-size",
+    16,
+    "--enable-dp-attention",
+    "--moe-a2a-backend",
+    "deepep",
+    "--deepep-mode",
+    "auto",
+    "--quantization",
+    "modelslim",
+    "--enable-dp-lm-head",
+    "--kv-cache-dtype",
+    "bfloat16",
+    "--speculative-algorithm",
+    "DSPARK",
+    "--speculative-draft-model-path",
+    DEEPSEEK_V4_FLASH_0731_W8A8_MODEL_PATH,
+    "--speculative-draft-model-quantization",
+    "modelslim",
+    "--speculative-draft-attention-backend",
+    "ascend",
+    "--speculative-num-draft-tokens",
+    6,
+    "--speculative-dspark-block-size",
+    5,
+    "--skip-server-warmup",
+    "--cuda-graph-bs",
+    1,
+    2,
+    4,
+    5,
+    6,
+]
+
+
+DEEPSEEK_V4_FLASH_W8A8_GENERATION_CONFIG_HIGH = {
+    "max_tokens": 125000,
+    "top_p": 1,
+    "temperature": 1,
+    "n": 1,
+    "extra_body": {
+        "chat_template_kwargs": {"thinking": True, "reasoning_effort": "high"}
+    },
+}
+
+
+class TestNPUDeepSeekV4FlashW8A88PGPQA(TestNpuAccuracyTestCaseBase):
+    """Test NPU accuracy for DeepSeek-V4-Flash W8A8 8p DSPARK GPQA."""
+
+    benchmark_tool = BENCHMARK_TOOL_DEFAULT
+    model = DEEPSEEK_V4_FLASH_0731_W8A8_MODEL_PATH
+    other_args = DEEPSEEK_V4_FLASH_W8A8_DSPARK_8P_OTHER_ARGS
+    envs = DEEPSEEK_V4_FLASH_W8A8_DSPARK_8P_ENVS
+    accuracy = 0.874
+    datasets = ["gpqa_diamond"]
+    few_shot_num = 0
+    generation_config = DEEPSEEK_V4_FLASH_W8A8_GENERATION_CONFIG_HIGH
+    eval_batch_size = 128
+    stream = True
+    timeout = 6000
+    seed = 1
+
+    def test_npu_deepseek_v4_flash_w8a8_8p_gpqa(self):
+        """Run NPU accuracy test for DeepSeek-V4-Flash W8A8 8p DSPARK GPQA."""
+        self.run_accuracy()
+
+
+if __name__ == "__main__":
+    unittest.main()
diff --git a/test/registered/npu/accuracy/glm5_2/test_npu_glm_5_2_w4a8_16p_gpqa.py b/test/registered/npu/accuracy/glm5_2/test_npu_glm_5_2_w4a8_16p_gpqa.py
index 5ddafd66e..044ae58c5 100644
--- a/test/registered/npu/accuracy/glm5_2/test_npu_glm_5_2_w4a8_16p_gpqa.py
+++ b/test/registered/npu/accuracy/glm5_2/test_npu_glm_5_2_w4a8_16p_gpqa.py
@@ -18,15 +18,17 @@ register_npu_ci(
 )
 
 GLM_5_2_W4A8_16P_TWO_NODE_ENVS = {
-    "SGLANG_SET_CPU_AFFINITY": "1",
+    "PYTORCH_NPU_ALLOC_CONF": "expandable_segments:True",
     "STREAMS_PER_DEVICE": "32",
-    "SGLANG_DISAGGREGATION_BOOTSTRAP_TIMEOUT": "600",
+    "SGLANG_SET_CPU_AFFINITY": "1",
     "SGLANG_ENABLE_SPEC_V2": "1",
     "SGLANG_ENABLE_OVERLAP_PLAN_STREAM": "1",
-    "SGLANG_DEEPEP_NUM_MAX_DISPATCH_TOKENS_PER_RANK": "32",
-    "TRANSFORMERS_VERBOSITY": "error",
-    "DEEP_NORMAL_MODE_USE_INT8_QUANT": "1",
     "DEEPEP_HCCL_BUFFSIZE": "2500",
+    "DEEPEP_NORMAL_COMBINE_ENABLE_LONG_SEQ": "1",
+    "DEEPEP_NORMAL_LONG_SEQ_PER_ROUND_TOKENS": "1024",
+    "DEEPEP_NORMAL_LONG_SEQ_ROUND": "72",
+    "SGLANG_DEEPEP_NUM_MAX_DISPATCH_TOKENS_PER_RANK": "32",
+    "DEEP_NORMAL_MODE_USE_INT8_QUANT": "1",
     "HCCL_SOCKET_IFNAME": NIC_NAME,
     "GLOO_SOCKET_IFNAME": NIC_NAME,
 }
@@ -40,32 +42,38 @@ GLM_5_2_W4A8_16P_TWO_NODE_OTHER_ARGS = [
     32,
     "--nnodes",
     2,
-    # "--dp-size",
-    # 8,
-    # "--enable-dp-attention",
+    "--dp-size",
+    8,
+    "--enable-dp-attention",
     "--chunked-prefill-size",
     65536,
     "--max-prefill-tokens",
     280000,
     "--trust-remote-code",
     "--mem-fraction-static",
-    0.70,
+    0.76,
+    "--context-length",
+    135000,
     "--served-model-name",
-    "glm-5",
+    "glm-5.2-w4a8",
     "--cuda-graph-max-bs",
-    32,
+    4,
     "--max-running-requests",
     32,
     "--quantization",
     "modelslim",
-    # "--speculative-draft-model-quantization",
-    # "unquant",
     "--moe-a2a-backend",
     "deepep",
     "--deepep-mode",
     "auto",
+    "--disable-shared-experts-fusion",
     "--load-balance-method",
     "round_robin",
+    "--reasoning-parser",
+    "glm45",
+    "--tool-call-parser",
+    "glm47",
+    "--enable-metrics",
     "--speculative-algorithm",
     "NEXTN",
     "--speculative-num-steps",
@@ -74,10 +82,6 @@ GLM_5_2_W4A8_16P_TWO_NODE_OTHER_ARGS = [
     1,
     "--speculative-num-draft-tokens",
     4,
-    "--reasoning-parser",
-    "glm45",
-    "--tool-call-parser",
-    "glm47",
 ]
 
 GLM_5_2_W4A8_16P_TWO_NODE_MODEL_CONFIG = {
@@ -94,8 +98,15 @@ class TestNPUGLM_5_2_W4A8_16P_GPQA(TestNpuAccuracyMultiNodePdMixTestCaseBase):
     model_config = GLM_5_2_W4A8_16P_TWO_NODE_MODEL_CONFIG
     accuracy = 0.912
     datasets = ["gpqa_diamond"]
+    # eval_batch_size = 16
+    # generation_config = {"max_tokens": 131072, "temperature": 1.0}
     eval_batch_size = 32
-    generation_config = {"max_tokens": 65536, "temperature": 1.0}
+    generation_config = {
+        "max_tokens": 65536,
+        "temperature": 1.0,
+        "timeout": 1200,
+        "stream": True,
+    }
 
     def test_npu_glm_5_2_w4a8_16p_gpqa(self):
         """Run NPU accuracy test for GLM-5.2-w4a8 16p two nodes on gpqa_diamond"""
diff --git a/test/registered/npu/accuracy/kimi_k3/test_npu_kimi_k3_w4a8_32p_gpqa.py b/test/registered/npu/accuracy/kimi_k3/test_npu_kimi_k3_w4a8_32p_gpqa.py
new file mode 100644
index 000000000..b3d8ae60d
--- /dev/null
+++ b/test/registered/npu/accuracy/kimi_k3/test_npu_kimi_k3_w4a8_32p_gpqa.py
@@ -0,0 +1,136 @@
+import unittest
+
+from sglang.test.ascend.e2e.test_npu_accuracy_utils import (
+    BENCHMARK_TOOL_DEFAULT,
+    TestNpuAccuracyMultiNodePdMixTestCaseBase,
+)
+from sglang.test.ascend.e2e.test_npu_multi_node_utils import NIC_NAME
+from sglang.test.ascend.e2e.test_npu_performance_utils import (
+    KIMI_K3_DSPARK_MODEL_PATH,
+    KIMI_K3_W4A8_MODEL_PATH,
+)
+from sglang.test.ci.ci_register import register_npu_ci
+
+register_npu_ci(
+    est_time=3600,
+    suite="",
+    nightly=True,
+    disabled="accuracy testcase",
+)
+
+KIMI_K3_W4A8_32P_ENVS = {
+    "SGLANG_SET_CPU_AFFINITY": "1",
+    "SGLANG_ONE_VISIBLE_DEVICE_PER_PROCESS": "1",
+    "SGLANG_NPU_USE_TRITON_PREFIX_KV_CACHE_STORE": "1",
+    "TRITON_CACHE_DIR": "/tmp/triton_cache",
+    "SGLANG_ENABLE_OVERLAP_PLAN_STREAM": "1",
+    "SGLANG_ENABLE_SPEC_V2": "1",
+    "SGLANG_RAGGED_VERIFY_MODE": "static",
+    "SGLANG_DSPARK_FOLDED_PROPOSAL": "0",
+    "SGLANG_DSPARK_FOLDED_SAMPLING": "0",
+    "SGLANG_DSPARK_STACKED_CTX_KV": "0",
+    "SGLANG_DSPARK_EMBED_IN_GRAPH": "0",
+    "PYTORCH_NPU_ALLOC_CONF": "expandable_segments:True",
+    "HCCL_SOCKET_IFNAME": NIC_NAME,
+    "GLOO_SOCKET_IFNAME": NIC_NAME,
+    "STREAMS_PER_DEVICE": "32",
+    "DEEP_NORMAL_MODE_USE_INT8_QUANT": "1",
+    "SGLANG_DEEPEP_NUM_MAX_DISPATCH_TOKENS_PER_RANK": "128",
+    "HCCL_BUFFSIZE": "2000",
+    "DEEPEP_NORMAL_LONG_SEQ_ROUND": "64",
+    "DEEPEP_NORMAL_LONG_SEQ_PER_ROUND_TOKENS": "512",
+    "HCCL_OP_EXPANSION_MODE": "AIV",
+}
+
+KIMI_K3_W4A8_32P_OTHER_ARGS = [
+    "--model-loader-extra-config",
+    '{"enable_multithread_load": true}',
+    "--nnodes",
+    4,
+    "--tokenizer-path",
+    KIMI_K3_W4A8_MODEL_PATH,
+    "--trust-remote-code",
+    "--attention-backend",
+    "ascend",
+    "--device",
+    "npu",
+    "--quantization",
+    "modelslim",
+    "--dtype",
+    "bfloat16",
+    "--tp-size",
+    64,
+    "--enable-dp-attention",
+    "--dp-size",
+    4,
+    "--enable-dp-lm-head",
+    "--enable-shared-experts-attn-tp",
+    "--enable-dense-mlp-attn-tp",
+    "--mem-fraction-static",
+    0.72,
+    "--chunked-prefill-size",
+    8192,
+    "--cuda-graph-bs",
+    1,
+    4,
+    16,
+    "--max-running-requests",
+    64,
+    "--reasoning-parser",
+    "kimi_k3",
+    "--moe-a2a-backend",
+    "deepep",
+    "--deepep-mode",
+    "auto",
+    "--speculative-algorithm",
+    "DSPARK",
+    "--speculative-draft-model-path",
+    KIMI_K3_DSPARK_MODEL_PATH,
+    "--speculative-draft-model-quantization",
+    "unquant",
+    "--speculative-dspark-block-size",
+    7,
+    "--speculative-draft-attention-backend",
+    "ascend",
+    "--linear-attn-verify-backend",
+    "triton",
+    "--speculative-eagle-topk",
+    1,
+    "--disable-radix-cache",
+    "--disable-custom-all-reduce",
+    "--watchdog-timeout",
+    9000,
+]
+
+KIMI_K3_W4A8_32P_MODEL_CONFIG = {
+    "model_path": KIMI_K3_W4A8_MODEL_PATH,
+    "other_args": KIMI_K3_W4A8_32P_OTHER_ARGS,
+    "node_envs": KIMI_K3_W4A8_32P_ENVS,
+}
+
+
+class TestNPUKimiK3_W4A8_32P_GPQA(TestNpuAccuracyMultiNodePdMixTestCaseBase):
+    """Test NPU accuracy for Kimi-K3-w4a8 32p four nodes on gpqa_diamond"""
+
+    benchmark_tool = BENCHMARK_TOOL_DEFAULT
+    model_config = KIMI_K3_W4A8_32P_MODEL_CONFIG
+    accuracy = 0.935
+    datasets = ["gpqa_diamond"]
+    few_shot_num = 0
+    eval_batch_size = 32
+    generation_config = {
+        "max_tokens": 131072,
+        "temperature": 1.0,
+        "top_p": 0.95,
+        "extra_body": {"reasoning_effort": "max"},
+    }
+    timeout = 10000
+    seed = 42
+
+    def test_npu_kimi_k3_w4a8_32p_gpqa(self):
+        """Run NPU accuracy test for Kimi-K3-w4a8 32p four nodes on gpqa_diamond"""
+        self.run_accuracy()
+
+
+if __name__ == "__main__":
+    unittest.main()
diff --git a/test/registered/npu/performance/deepseek_v4_flash/test_npu_deepseek_v4_flash_w8a8_1p1d_16p_in8k_out1k_50ms.py b/test/registered/npu/performance/deepseek_v4_flash/test_npu_deepseek_v4_flash_w8a8_1p1d_16p_in8k_out1k_50ms.py
index 0f8f5f460..bb02ffff1 100644
--- a/test/registered/npu/performance/deepseek_v4_flash/test_npu_deepseek_v4_flash_w8a8_1p1d_16p_in8k_out1k_50ms.py
+++ b/test/registered/npu/performance/deepseek_v4_flash/test_npu_deepseek_v4_flash_w8a8_1p1d_16p_in8k_out1k_50ms.py
@@ -3,7 +3,7 @@ import unittest
 from sglang.test.ascend.e2e.test_npu_performance_utils import (
     AISBENCHMARK_DATASET_DEFAULT,
     BENCHMARK_TOOL_DEFAULT,
-    DEEPSEEK_V4_FLASH_W8A8_MTP_MODEL_PATH,
+    DEEPSEEK_V4_FLASH_0731_W8A8_MODEL_PATH,
     TestNpuPerfMultiNodePdSepTestCaseBase,
 )
 from sglang.test.ci.ci_register import register_npu_ci
@@ -195,7 +195,7 @@ DEEPSEEK_V4_FLASH_W8A8_1P1D_DECODE_ARGS = [
 
 # Model config for DSV4-Flash W8A8 1P+1D PD-Sep deployment.
 DEEPSEEK_V4_FLASH_W8A8_1P1D_MODEL_CONFIG = {
-    "model_path": DEEPSEEK_V4_FLASH_W8A8_MTP_MODEL_PATH,
+    "model_path": DEEPSEEK_V4_FLASH_0731_W8A8_MODEL_PATH,
     "prefill_args": DEEPSEEK_V4_FLASH_W8A8_1P1D_PREFILL_ARGS,
     "decode_args": DEEPSEEK_V4_FLASH_W8A8_1P1D_DECODE_ARGS,
     "prefill_envs": DEEPSEEK_V4_FLASH_W8A8_1P1D_PREFILL_ENVS,
diff --git a/test/registered/npu/performance/deepseek_v4_flash/test_npu_deepseek_v4_flash_w8a8_8p_in32k_out1k_50ms.py b/test/registered/npu/performance/deepseek_v4_flash/test_npu_deepseek_v4_flash_w8a8_8p_in32k_out1k_50ms.py
index a4704fbdd..fb560543d 100644
--- a/test/registered/npu/performance/deepseek_v4_flash/test_npu_deepseek_v4_flash_w8a8_8p_in32k_out1k_50ms.py
+++ b/test/registered/npu/performance/deepseek_v4_flash/test_npu_deepseek_v4_flash_w8a8_8p_in32k_out1k_50ms.py
@@ -3,7 +3,7 @@ import unittest
 from sglang.test.ascend.e2e.test_npu_performance_utils import (
     AISBENCHMARK_DATASET_DEFAULT,
     BENCHMARK_TOOL_DEFAULT,
-    DEEPSEEK_V4_FLASH_W8A8_MTP_MODEL_PATH,
+    DEEPSEEK_V4_FLASH_0731_W8A8_MODEL_PATH,
     TestNpuPerformanceTestCaseBase,
 )
 from sglang.test.ci.ci_register import register_npu_ci
@@ -116,7 +116,7 @@ class TestNPUDeepSeekV4FlashW8A88PIn32kOut1k50ms(TestNpuPerformanceTestCaseBase)
 
     benchmark_tool = BENCHMARK_TOOL_DEFAULT
     dataset_type = AISBENCHMARK_DATASET_DEFAULT
-    model = DEEPSEEK_V4_FLASH_W8A8_MTP_MODEL_PATH
+    model = DEEPSEEK_V4_FLASH_0731_W8A8_MODEL_PATH
     other_args = DEEPSEEK_V4_FLASH_W8A8_8P_OTHER_ARGS
     envs = DEEPSEEK_V4_FLASH_W8A8_8P_ENVS
     dataset_name = "random"
diff --git a/test/registered/npu/performance/deepseek_v4_flash/test_npu_deepseek_v4_flash_w8a8_8p_in8k_out1k_50ms.py b/test/registered/npu/performance/deepseek_v4_flash/test_npu_deepseek_v4_flash_w8a8_8p_in8k_out1k_50ms.py
index 288fc031a..22f2209d7 100644
--- a/test/registered/npu/performance/deepseek_v4_flash/test_npu_deepseek_v4_flash_w8a8_8p_in8k_out1k_50ms.py
+++ b/test/registered/npu/performance/deepseek_v4_flash/test_npu_deepseek_v4_flash_w8a8_8p_in8k_out1k_50ms.py
@@ -3,7 +3,7 @@ import unittest
 from sglang.test.ascend.e2e.test_npu_performance_utils import (
     AISBENCHMARK_DATASET_DEFAULT,
     BENCHMARK_TOOL_DEFAULT,
-    DEEPSEEK_V4_FLASH_W8A8_MTP_MODEL_PATH,
+    DEEPSEEK_V4_FLASH_0731_W8A8_MODEL_PATH,
     TestNpuPerformanceTestCaseBase,
 )
 from sglang.test.ci.ci_register import register_npu_ci
@@ -117,7 +117,7 @@ class TestNPUDeepSeekV4FlashW8A88PIn8kOut1k50ms(TestNpuPerformanceTestCaseBase):
 
     benchmark_tool = BENCHMARK_TOOL_DEFAULT
     dataset_type = AISBENCHMARK_DATASET_DEFAULT
-    model = DEEPSEEK_V4_FLASH_W8A8_MTP_MODEL_PATH
+    model = DEEPSEEK_V4_FLASH_0731_W8A8_MODEL_PATH
     other_args = DEEPSEEK_V4_FLASH_W8A8_8P_OTHER_ARGS
     envs = DEEPSEEK_V4_FLASH_W8A8_8P_ENVS
     dataset_name = "random"