[MoE Refactor] Add Temporary Integration Tests - H100/B200 (#31759)

Signed-off-by: Robert Shaw <robshaw@redhat.com>
Co-authored-by: Robert Shaw <robshaw@redhat.com>

.buildkite/test-pipeline.yaml

@@ -1406,3 +1406,19 @@ steps:
   working_dir: "/vllm-workspace"
   commands:
   - bash .buildkite/scripts/scheduled_integration_test/qwen30b_a3b_fp8_block_ep_eplb.sh 0.8 200 8020 2 1
+
+##### MoE Refactor (Temporary) Tests #####
+
+- label: MoE Refactor Integration Test (H100 - TEMPORARY) # optional
+  gpu: h100
+  optional: true
+  num_gpus: 2
+  commands:
+    - pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=evals/gsm8k/configs/moe-refactor/config-h100.txt
+  
+- label: MoE Refactor Integration Test (B200 - TEMPORARY) # optional
+  gpu: b200
+  optional: true
+  num_gpus: 2
+  commands:
+    - pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=evals/gsm8k/configs/moe-refactor/config-b200.txt

tests/evals/gsm8k/configs/moe-refactor/Llama-4-Scout-Fp8-ModelOpt-fi-cutlass.yaml

+model_name: "nvidia/Llama-4-Scout-17B-16E-Instruct-FP8"
+accuracy_threshold: 0.92
+num_questions: 1319
+num_fewshot: 5
+server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2"
+env:
+  VLLM_USE_FLASHINFER_MOE_FP8: "1"
+  VLLM_FLASHINFER_MOE_BACKEND: "throughput"

tests/evals/gsm8k/configs/moe-refactor/Llama-4-Scout-Fp8-ModelOpt-fi-trtllm.yaml

+model_name: "nvidia/Llama-4-Scout-17B-16E-Instruct-FP8"
+accuracy_threshold: 0.92
+num_questions: 1319
+num_fewshot: 5
+server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2"
+env:
+  VLLM_USE_FLASHINFER_MOE_FP8: "1"
+  VLLM_FLASHINFER_MOE_BACKEND: "latency"

tests/evals/gsm8k/configs/moe-refactor/Llama-4-Scout-Fp8-ModelOpt-marlin.yaml

+model_name: "nvidia/Llama-4-Scout-17B-16E-Instruct-FP8"
+accuracy_threshold: 0.92
+num_questions: 1319
+num_fewshot: 5
+server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2"
+env:
+  VLLM_TEST_FORCE_FP8_MARLIN: "1"

tests/evals/gsm8k/configs/moe-refactor/Llama-4-Scout-Fp8-ModelOpt-triton.yaml

+model_name: "nvidia/Llama-4-Scout-17B-16E-Instruct-FP8"
+accuracy_threshold: 0.92
+num_questions: 1319
+num_fewshot: 5
+server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2"

tests/evals/gsm8k/configs/moe-refactor/Mixtral-8x7B-Fp8-AutoFp8-fi-cutlass.yaml

+# TODO(rob): enable
+# model_name: "amd/Mixtral-8x7B-Instruct-v0.1-FP8-KV"
+# accuracy_threshold: 0.62
+# num_questions: 1319
+# num_fewshot: 5
+# server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2"
+# env:
+#   VLLM_USE_FLASHINFER_MOE_FP8: "1"
+#   VLLM_FLASHINFER_MOE_BACKEND: "throughput"

tests/evals/gsm8k/configs/moe-refactor/Mixtral-8x7B-Fp8-AutoFp8-triton.yaml

+model_name: "amd/Mixtral-8x7B-Instruct-v0.1-FP8-KV"
+accuracy_threshold: 0.62
+num_questions: 1319
+num_fewshot: 5
+server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2"

tests/evals/gsm8k/configs/moe-refactor/Qwen3-30B-A3B-Fp8-AutoFp8-deepgemm.yaml

+model_name: "Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8"
+accuracy_threshold: 0.88
+num_questions: 1319
+num_fewshot: 5
+server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2"
+env:
+  VLLM_USE_DEEP_GEMM: "1"
+  VLLM_USE_DEEP_GEMM_MOE: "1"

tests/evals/gsm8k/configs/moe-refactor/Qwen3-30B-A3B-Fp8-AutoFp8-fi-cutlass.yaml

+model_name: "Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8"
+accuracy_threshold: 0.88
+num_questions: 1319
+num_fewshot: 5
+server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2"
+env:
+  VLLM_USE_DEEP_GEMM: "0"
+  VLLM_USE_DEEP_GEMM_MOE: "0"
+  VLLM_USE_FLASHINFER_MOE_FP8: "1"
+  VLLM_FLASHINFER_MOE_BACKEND: "throughput"

tests/evals/gsm8k/configs/moe-refactor/Qwen3-30B-A3B-Fp8-AutoFp8-fi-trtllm.yaml

+model_name: "Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8"
+accuracy_threshold: 0.88
+num_questions: 1319
+num_fewshot: 5
+server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2"
+env:
+  VLLM_USE_DEEP_GEMM: "0"
+  VLLM_USE_DEEP_GEMM_MOE: "0"
+  VLLM_USE_FLASHINFER_MOE_FP8: "1"
+  VLLM_FLASHINFER_MOE_BACKEND: "latency"

tests/evals/gsm8k/configs/moe-refactor/Qwen3-30B-A3B-Fp8-AutoFp8-marlin.yaml

+model_name: "Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8"
+accuracy_threshold: 0.88
+num_questions: 1319
+num_fewshot: 5
+server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2"
+env:
+  VLLM_USE_DEEP_GEMM: "0"
+  VLLM_USE_DEEP_GEMM_MOE: "0"
+  VLLM_TEST_FORCE_FP8_MARLIN: "1"

tests/evals/gsm8k/configs/moe-refactor/Qwen3-30B-A3B-Fp8-AutoFp8-triton.yaml

+model_name: "Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8"
+accuracy_threshold: 0.88
+num_questions: 1319
+num_fewshot: 5
+server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2"
+env:
+  VLLM_USE_DEEP_GEMM: "0"
+  VLLM_USE_DEEP_GEMM_MOE: "0"

tests/evals/gsm8k/configs/moe-refactor/Qwen3-30B-A3B-Fp8-CT-Block-deepgemm.yaml

+model_name: "RedHatAI/Qwen3-30B-A3B-FP8-block"
+accuracy_threshold: 0.85
+num_questions: 1319
+num_fewshot: 5
+server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2"
+env:
+  VLLM_USE_DEEP_GEMM: "1"
+  VLLM_USE_DEEP_GEMM_MOE: "1"

tests/evals/gsm8k/configs/moe-refactor/Qwen3-30B-A3B-Fp8-CT-Block-fi-cutlass.yaml

+model_name: "RedHatAI/Qwen3-30B-A3B-FP8-block"
+accuracy_threshold: 0.85
+num_questions: 1319
+num_fewshot: 5
+server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2"
+env:
+  VLLM_USE_DEEP_GEMM: "0"
+  VLLM_USE_DEEP_GEMM_MOE: "0"
+  VLLM_USE_FLASHINFER_MOE_FP8: "1"
+  VLLM_FLASHINFER_MOE_BACKEND: "throughput"

tests/evals/gsm8k/configs/moe-refactor/Qwen3-30B-A3B-Fp8-CT-Block-marlin.yaml

+model_name: "RedHatAI/Qwen3-30B-A3B-FP8-block"
+accuracy_threshold: 0.85
+num_questions: 1319
+num_fewshot: 5
+server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2"
+env:
+  VLLM_USE_DEEP_GEMM: "0"
+  VLLM_USE_DEEP_GEMM_MOE: "0"
+  VLLM_TEST_FORCE_FP8_MARLIN: "1"

tests/evals/gsm8k/configs/moe-refactor/Qwen3-30B-A3B-Fp8-CT-Block-vllm-cutlass.yaml

+model_name: "RedHatAI/Qwen3-30B-A3B-FP8-block"
+accuracy_threshold: 0.85
+num_questions: 1319
+num_fewshot: 5
+server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2"
+env:
+  VLLM_USE_DEEP_GEMM: "0"
+  VLLM_USE_DEEP_GEMM_MOE: "0"

tests/evals/gsm8k/configs/moe-refactor/Qwen3-30B-A3B-Fp8-CT-Channel-marlin.yaml

+model_name: "RedHatAI/Qwen3-30B-A3B-FP8-dynamic"
+accuracy_threshold: 0.85
+num_questions: 1319
+num_fewshot: 5
+server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2"
+env:
+  VLLM_TEST_FORCE_FP8_MARLIN: "1"

tests/evals/gsm8k/configs/moe-refactor/Qwen3-30B-A3B-Fp8-CT-Channel-vllm-cutlass.yaml

+model_name: "RedHatAI/Qwen3-30B-A3B-FP8-dynamic"
+accuracy_threshold: 0.85
+num_questions: 1319
+num_fewshot: 5
+server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2"

tests/evals/gsm8k/configs/moe-refactor/Qwen3-30B-A3B-NvFp4-CT-fi-cutlass-dp-ep.yaml

+model_name: "RedHatAI/Qwen3-30B-A3B-NVFP4"
+accuracy_threshold: 0.88
+num_questions: 1319
+num_fewshot: 5
+server_args: "--enforce-eager --max-model-len 8192 --data-parallel-size 2 --enable-expert-parallel"
+env:
+  VLLM_USE_FLASHINFER_MOE_FP4: "1"
+  VLLM_FLASHINFER_MOE_BACKEND: "throughput"

tests/evals/gsm8k/configs/moe-refactor/Qwen3-30B-A3B-NvFp4-CT-fi-cutlass.yaml

+model_name: "RedHatAI/Qwen3-30B-A3B-NVFP4"
+accuracy_threshold: 0.88
+num_questions: 1319
+num_fewshot: 5
+server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2"
+env:
+  VLLM_USE_FLASHINFER_MOE_FP4: "1"
+  VLLM_FLASHINFER_MOE_BACKEND: "throughput"