CI: add fp8/fp4 ci on Qwen3-30B-A3B

tests/integration/defs/accuracy/references/gsm8k.yaml

@@ -53,5 +53,11 @@ deepseek-ai/DeepSeek-R1:
 Qwen3/Qwen3-30B-A3B:
   - quant_algo: FP8_BLOCK_SCALES
     accuracy: 84.36
+  - quant_algo: FP8
+    kv_cache_quant_algo: FP8
+    accuracy: 83.43
+  - quant_algo: NVFP4
+    kv_cache_quant_algo: FP8
+    accuracy: 83.43
 nvidia/Llama-3_3-Nemotron-Super-49B-v1:
   - accuracy: 92.57

tests/integration/defs/accuracy/references/mmlu.yaml

@@ -103,6 +103,12 @@ Qwen3/Qwen3-8B:
 Qwen3/Qwen3-30B-A3B:
   - quant_algo: FP8_BLOCK_SCALES
     accuracy: 79.53
+  - quant_algo: FP8
+    kv_cache_quant_algo: FP8
+    accuracy: 80.65
+  - quant_algo: NVFP4
+    kv_cache_quant_algo: FP8
+    accuracy: 80.65
 nvidia/Llama-3_3-Nemotron-Super-49B-v1:
   - accuracy: 79.43
 nvidia/Llama-3.1-Nemotron-Nano-8B-v1:

tests/integration/defs/accuracy/test_llm_api_pytorch.py

@@ -779,6 +779,54 @@ def test_fp8_block_scales(self, tp_size, pp_size, ep_size, attention_dp,
             task = GSM8K(self.MODEL_NAME)
             task.evaluate(llm)
 
+    @skip_pre_hopper
+    @pytest.mark.parametrize(
+        "tp_size,pp_size,ep_size,attention_dp,cuda_graph,overlap_scheduler",
+        [(1, 1, 1, True, True, True)],
+        ids=["latency"])
+    def test_fp8(self, tp_size, pp_size, ep_size, attention_dp, cuda_graph,
+                 overlap_scheduler):
+        pytorch_config = PyTorchConfig(
+            enable_overlap_scheduler=overlap_scheduler,
+            use_cuda_graph=cuda_graph)
+
+        llm = LLM(
+            f"{llm_models_root()}/Qwen3/saved_models_Qwen3-30B-A3B_fp8_hf",
+            tensor_parallel_size=tp_size,
+            pipeline_parallel_size=pp_size,
+            moe_expert_parallel_size=ep_size,
+            pytorch_backend_config=pytorch_config,
+            enable_attention_dp=attention_dp)
+        with llm:
+            task = MMLU(self.MODEL_NAME)
+            task.evaluate(llm)
+            task = GSM8K(self.MODEL_NAME)
+            task.evaluate(llm)
+
+    @skip_pre_hopper
+    @pytest.mark.parametrize(
+        "tp_size,pp_size,ep_size,attention_dp,cuda_graph,overlap_scheduler",
+        [(1, 1, 1, True, True, True)],
+        ids=["latency"])
+    def test_nvfp4(self, tp_size, pp_size, ep_size, attention_dp, cuda_graph,
+                   overlap_scheduler):
+        pytorch_config = PyTorchConfig(
+            enable_overlap_scheduler=overlap_scheduler,
+            use_cuda_graph=cuda_graph)
+
+        llm = LLM(
+            f"{llm_models_root()}/Qwen3/saved_models_Qwen3-30B-A3B_nvfp4_hf",
+            tensor_parallel_size=tp_size,
+            pipeline_parallel_size=pp_size,
+            moe_expert_parallel_size=ep_size,
+            pytorch_backend_config=pytorch_config,
+            enable_attention_dp=attention_dp)
+        with llm:
+            task = MMLU(self.MODEL_NAME)
+            task.evaluate(llm)
+            task = GSM8K(self.MODEL_NAME)
+            task.evaluate(llm)
+
 
 class TestQwen3_32B(LlmapiAccuracyTestHarness):
     MODEL_NAME = "Qwen3/Qwen3-32B"

tests/integration/test_lists/test-db/l0_b200.yml

@@ -31,6 +31,7 @@ l0_b200:
   - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=False-attention_dp=False-cuda_graph=True-overlap_scheduler=False]
   - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=True]
   - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_nvfp4[fp8kv=True-attention_dp=True-cuda_graph=True-overlap_scheduler=True]
+  - accuracy/test_llm_api_pytorch.py::TestQwen3_30B_A3B::test_nvfp4[latency]
   - test_e2e.py::test_ptp_quickstart_advanced[Llama3.1-8B-NVFP4-nvfp4-quantized/Meta-Llama-3.1-8B]
   - test_e2e.py::test_ptp_quickstart_advanced[Llama3.1-8B-FP8-llama-3.1-model/Llama-3.1-8B-Instruct-FP8]
   - test_e2e.py::test_ptq_quickstart_advanced_mtp[DeepSeek-V3-Lite-BF16-DeepSeek-V3-Lite/bf16]

tests/integration/test_lists/test-db/l0_h100.yml

@@ -45,7 +45,7 @@ l0_h100:
   - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-fp8kv=False-attention_dp=False-cuda_graph=False-overlap_scheduler=True]
   - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_fp8_block_scales[mtp_nextn=2-fp8kv=True-attention_dp=True-cuda_graph=True-overlap_scheduler=True]
   - accuracy/test_llm_api_pytorch.py::TestQwen3_8B::test_fp8_block_scales[latency]
-  - accuracy/test_llm_api_pytorch.py::TestQwen3_30B_A3B::test_fp8_block_scales[latency]
+  - accuracy/test_llm_api_pytorch.py::TestQwen3_30B_A3B::test_fp8[latency]
   - accuracy/test_disaggregated_serving.py::TestLlama3_1_8B::test_auto_dtype[False]
   - accuracy/test_disaggregated_serving.py::TestLlama3_1_8B::test_auto_dtype[True]
   - test_e2e.py::test_trtllm_bench_pytorch_backend_sanity[meta-llama/Llama-3.1-8B-llama-3.1-8b-False-False]
@@ -186,6 +186,7 @@ l0_h100:
   - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=False-cuda_graph=True-overlap_scheduler=False]
   - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=False-cuda_graph=False-overlap_scheduler=True]
   - accuracy/test_llm_api_pytorch.py::TestDeepSeekV3Lite::test_bfloat16[mtp_nextn=2-attention_dp=True-cuda_graph=True-overlap_scheduler=True]
+  - accuracy/test_llm_api_pytorch.py::TestQwen3_30B_A3B::test_fp8_block_scales[latency]
 - condition:
     ranges:
       system_gpu_count: