[UX] Add --moe-backend arg for explicit kernel selection

tests/evals/gsm8k/configs/Qwen3-Next-80B-A3B-NVFP4-EP2.yaml

@@ -8,5 +8,4 @@ server_args: >-
   --tensor-parallel-size 2
   --enable-expert-parallel
   --speculative-config '{"method":"qwen3_next_mtp","num_speculative_tokens":1}'
-env:
-  VLLM_USE_FLASHINFER_MOE_FP4: "1"
+  --moe-backend=flashinfer_trtllm

tests/evals/gsm8k/configs/Qwen3-Next-FP8-EP2.yaml

@@ -7,5 +7,4 @@ server_args: >-
   --tensor-parallel-size 2
   --enable-expert-parallel
   --async-scheduling
-env:
-  VLLM_USE_FLASHINFER_MOE_FP8: "1"
+  --moe-backend=flashinfer_trtllm

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

@@ -2,7 +2,6 @@ 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 --data-parallel-size 2 --enable-expert-parallel"
+server_args: "--enforce-eager --max-model-len 8192 --data-parallel-size 2 --enable-expert-parallel --moe-backend=triton"
 env:
-  VLLM_USE_FLASHINFER_MOE_FP8: "0"
   VLLM_USE_DEEP_GEMM: "0"

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

@@ -2,7 +2,4 @@ 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 --all2all-backend deepep_low_latency"
-env:
-  VLLM_USE_FLASHINFER_MOE_FP4: "1"
-  VLLM_FLASHINFER_MOE_BACKEND: "masked_gemm"
+server_args: "--enforce-eager --max-model-len 8192 --data-parallel-size 2 --enable-expert-parallel --all2all-backend deepep_low_latency --moe-backend=flashinfer_cutedsl"

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

@@ -2,7 +2,4 @@ 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"
+server_args: "--enforce-eager --max-model-len 8192 --data-parallel-size 2 --enable-expert-parallel --moe-backend=flashinfer_cutlass"

tests/evals/gsm8k/configs/moe-refactor-dp-ep/Qwen3-30B-A3B-NvFp4-ModelOpt-fi-cutedsl-deepep-ll.yaml

@@ -2,7 +2,4 @@ model_name: "nvidia/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 --all2all-backend deepep_low_latency"
-env:
-  VLLM_USE_FLASHINFER_MOE_FP4: "1"
-  VLLM_FLASHINFER_MOE_BACKEND: "masked_gemm"
+server_args: "--enforce-eager --max-model-len 8192 --data-parallel-size 2 --enable-expert-parallel --all2all-backend deepep_low_latency --moe-backend=flashinfer_cutedsl"

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

@@ -2,7 +2,4 @@ model_name: "nvidia/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"
+server_args: "--enforce-eager --max-model-len 8192 --data-parallel-size 2 --enable-expert-parallel --moe-backend=flashinfer_cutlass"

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

@@ -2,7 +2,4 @@ model_name: "nvidia/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: "latency"
+server_args: "--enforce-eager --max-model-len 8192 --data-parallel-size 2 --enable-expert-parallel --moe-backend=flashinfer_trtllm"

tests/evals/gsm8k/configs/moe-refactor/Llama-4-Scout-BF16-fi-cutlass.yaml

@@ -2,8 +2,4 @@ model_name: "meta-llama/Llama-4-Scout-17B-16E-Instruct"
 accuracy_threshold: 0.92
 num_questions: 1319
 num_fewshot: 5
-server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --enable-expert-parallel"
-env:
-  VLLM_USE_FLASHINFER_MOE_FP16: "1"
-  VLLM_FLASHINFER_MOE_BACKEND: "throughput"
-
+server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --enable-expert-parallel --moe-backend=flashinfer_cutlass"

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

@@ -2,7 +2,4 @@ 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"
+server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --moe-backend=flashinfer_cutlass"

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

@@ -2,7 +2,4 @@ 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"
+server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --moe-backend=flashinfer_trtllm"

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

@@ -2,6 +2,4 @@ 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: "0"
+server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --moe-backend=triton"

tests/evals/gsm8k/configs/moe-refactor/Mixtral-8x7B-BF16-fi-cutlass.yaml

@@ -2,7 +2,4 @@ model_name: "mistralai/Mixtral-8x7B-v0.1"
 accuracy_threshold: 0.58
 num_questions: 1319
 num_fewshot: 5
-server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --enable-expert-parallel"
-env:
-  VLLM_USE_FLASHINFER_MOE_FP16: "1"
-  VLLM_FLASHINFER_MOE_BACKEND: "throughput"
+server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --enable-expert-parallel --moe-backend=flashinfer_cutlass"

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

@@ -3,7 +3,4 @@
 # 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"
+# server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --moe-backend=flashinfer_cutlass"

tests/evals/gsm8k/configs/moe-refactor/Nemotron-Nano-30B-Fp8-ModelOpt-fi-trtllm.yaml

@@ -2,7 +2,4 @@ model_name: "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-FP8"
 accuracy_threshold: 0.29
 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"
+server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --moe-backend=flashinfer_trtllm"

tests/evals/gsm8k/configs/moe-refactor/Nemotron-Nano-30B-NvFp4-ModelOpt-fi-cutlass.yaml

@@ -2,7 +2,4 @@ model_name: "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-NVFP4"
 accuracy_threshold: 0.29
 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"
+server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --moe-backend=flashinfer_cutlass"

tests/evals/gsm8k/configs/moe-refactor/Qwen3-30B-A3B-BF16-fi-cutlass.yaml

@@ -2,6 +2,4 @@ model_name: "Qwen/Qwen3-30B-A3B"
 accuracy_threshold: 0.88
 num_questions: 1319
 num_fewshot: 5
-server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --enable-expert-parallel"
-env:
-  VLLM_USE_FLASHINFER_MOE_FP16: "1"
+server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --enable-expert-parallel --moe-backend=flashinfer_cutlass"

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

@@ -2,7 +2,4 @@ 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_FLASHINFER_MOE_FP8: "1"
-  VLLM_FLASHINFER_MOE_BACKEND: "throughput"
+server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --moe-backend=flashinfer_cutlass"

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

@@ -2,7 +2,4 @@ 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_FLASHINFER_MOE_FP8: "1"
-  VLLM_FLASHINFER_MOE_BACKEND: "latency"
+server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --moe-backend=flashinfer_trtllm"

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

@@ -2,7 +2,6 @@ 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"
+server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --moe-backend=triton"
 env:
-  VLLM_USE_FLASHINFER_MOE_FP8: "0"
   VLLM_USE_DEEP_GEMM: "0"

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

@@ -2,7 +2,4 @@ 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_FLASHINFER_MOE_FP8: "1"
-  VLLM_FLASHINFER_MOE_BACKEND: "throughput"
+server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --moe-backend=flashinfer_cutlass"

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

@@ -2,7 +2,6 @@ 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"
+server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --moe-backend=triton"
 env:
-  VLLM_USE_FLASHINFER_MOE_FP8: "0"
   VLLM_USE_DEEP_GEMM: "0"

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

@@ -2,7 +2,4 @@ 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"
+server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --moe-backend=flashinfer_cutlass"

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

@@ -2,7 +2,4 @@ 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: "latency"
+server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --moe-backend=flashinfer_trtllm"

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

@@ -2,6 +2,4 @@ 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: "0"
+server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --moe-backend=cutlass"

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

@@ -2,7 +2,4 @@ model_name: "nvidia/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"
+server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --moe-backend=flashinfer_cutlass"

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

@@ -2,7 +2,4 @@ model_name: "nvidia/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: "latency"
+server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --moe-backend=flashinfer_trtllm"

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

@@ -2,6 +2,4 @@ model_name: "nvidia/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: "0"
+server_args: "--enforce-eager --max-model-len 8192 --tensor-parallel-size 2 --moe-backend=cutlass"

tests/quantization/test_blackwell_moe.py

@@ -85,43 +85,46 @@ def can_initialize(
     )
 )
 def test_llama4_fp8_tensor_moe_flashinfer_cutlass(monkeypatch: pytest.MonkeyPatch):
-    monkeypatch.setenv("VLLM_USE_FLASHINFER_MOE_FP8", "1")
-    monkeypatch.setenv("VLLM_FLASHINFER_MOE_BACKEND", "throughput")
     can_initialize(
-        "nvidia/Llama-4-Scout-17B-16E-Instruct-FP8", hf_overrides=HF_OVERRIDE_MM
+        "nvidia/Llama-4-Scout-17B-16E-Instruct-FP8",
+        hf_overrides=HF_OVERRIDE_MM,
+        extra_args=["--moe-backend=flashinfer_cutlass"],
     )
 
 
 def test_llama4_fp8_tensor_moe_flashinfer_trtllm(monkeypatch: pytest.MonkeyPatch):
-    monkeypatch.setenv("VLLM_USE_FLASHINFER_MOE_FP8", "1")
-    monkeypatch.setenv("VLLM_FLASHINFER_MOE_BACKEND", "latency")
     can_initialize(
-        "nvidia/Llama-4-Scout-17B-16E-Instruct-FP8", hf_overrides=HF_OVERRIDE_MM
+        "nvidia/Llama-4-Scout-17B-16E-Instruct-FP8",
+        hf_overrides=HF_OVERRIDE_MM,
+        extra_args=["--moe-backend=flashinfer_trtllm"],
     )
 
 
 def test_llama4_nvfp4_moe_flashinfer_cutlass(monkeypatch: pytest.MonkeyPatch):
-    monkeypatch.setenv("VLLM_USE_FLASHINFER_MOE_FP4", "1")
-    monkeypatch.setenv("VLLM_FLASHINFER_MOE_BACKEND", "throughput")
     can_initialize(
-        "nvidia/Llama-4-Scout-17B-16E-Instruct-FP4", hf_overrides=HF_OVERRIDE_MM
+        "nvidia/Llama-4-Scout-17B-16E-Instruct-FP4",
+        hf_overrides=HF_OVERRIDE_MM,
+        extra_args=["--moe-backend=flashinfer_cutlass"],
     )
 
 
 def test_llama4_nvfp4_moe_flashinfer_trtllm(monkeypatch: pytest.MonkeyPatch):
-    monkeypatch.setenv("VLLM_USE_FLASHINFER_MOE_FP4", "1")
-    monkeypatch.setenv("VLLM_FLASHINFER_MOE_BACKEND", "latency")
     can_initialize(
-        "nvidia/Llama-4-Scout-17B-16E-Instruct-FP4", hf_overrides=HF_OVERRIDE_MM
+        "nvidia/Llama-4-Scout-17B-16E-Instruct-FP4",
+        hf_overrides=HF_OVERRIDE_MM,
+        extra_args=["--moe-backend=flashinfer_trtllm"],
     )
 
 
 ## DeepSeekV3 ##
 
 
 def test_deepseek_fp8_block_moe_deep_gemm(monkeypatch: pytest.MonkeyPatch):
-    monkeypatch.setenv("VLLM_USE_DEEP_GEMM", "1")
-    can_initialize("deepseek-ai/DeepSeek-V3.1", hf_overrides=HF_OVERRIDE_TEXT)
+    can_initialize(
+        "deepseek-ai/DeepSeek-V3.1",
+        hf_overrides=HF_OVERRIDE_TEXT,
+        extra_args=["--moe-backend=deep_gemm"],
+    )
 
 
 @pytest.mark.skip(
@@ -131,27 +134,35 @@ def test_deepseek_fp8_block_moe_deep_gemm(monkeypatch: pytest.MonkeyPatch):
     )
 )
 def test_deepseek_fp8_block_moe_flashinfer_cutlass(monkeypatch: pytest.MonkeyPatch):
-    monkeypatch.setenv("VLLM_USE_FLASHINFER_MOE_FP8", "1")
-    monkeypatch.setenv("VLLM_FLASHINFER_MOE_BACKEND", "throughput")
-    can_initialize("deepseek-ai/DeepSeek-V3.1", hf_overrides=HF_OVERRIDE_TEXT)
+    can_initialize(
+        "deepseek-ai/DeepSeek-V3.1",
+        hf_overrides=HF_OVERRIDE_TEXT,
+        extra_args=["--moe-backend=flashinfer_cutlass"],
+    )
 
 
 def test_deepseek_fp8_block_moe_flashinfer_trtllm(monkeypatch: pytest.MonkeyPatch):
-    monkeypatch.setenv("VLLM_USE_FLASHINFER_MOE_FP8", "1")
-    monkeypatch.setenv("VLLM_FLASHINFER_MOE_BACKEND", "latency")
-    can_initialize("deepseek-ai/DeepSeek-V3.1", hf_overrides=HF_OVERRIDE_TEXT)
+    can_initialize(
+        "deepseek-ai/DeepSeek-V3.1",
+        hf_overrides=HF_OVERRIDE_TEXT,
+        extra_args=["--moe-backend=flashinfer_trtllm"],
+    )
 
 
 def test_deepseek_nvfp4_moe_flashinfer_cutlass(monkeypatch: pytest.MonkeyPatch):
-    monkeypatch.setenv("VLLM_USE_FLASHINFER_MOE_FP4", "1")
-    monkeypatch.setenv("VLLM_FLASHINFER_MOE_BACKEND", "throughput")
-    can_initialize("nvidia/DeepSeek-R1-0528-FP4-v2", hf_overrides=HF_OVERRIDE_TEXT)
+    can_initialize(
+        "nvidia/DeepSeek-R1-0528-FP4-v2",
+        hf_overrides=HF_OVERRIDE_TEXT,
+        extra_args=["--moe-backend=flashinfer_cutlass"],
+    )
 
 
 def test_deepseek_nvfp4_moe_flashinfer_trtllm(monkeypatch: pytest.MonkeyPatch):
-    monkeypatch.setenv("VLLM_USE_FLASHINFER_MOE_FP4", "1")
-    monkeypatch.setenv("VLLM_FLASHINFER_MOE_BACKEND", "latency")
-    can_initialize("nvidia/DeepSeek-R1-0528-FP4-v2", hf_overrides=HF_OVERRIDE_TEXT)
+    can_initialize(
+        "nvidia/DeepSeek-R1-0528-FP4-v2",
+        hf_overrides=HF_OVERRIDE_TEXT,
+        extra_args=["--moe-backend=flashinfer_trtllm"],
+    )
 
 
 ## GPT-OSS ##
@@ -184,5 +195,8 @@ def test_gptoss_eager(monkeypatch: pytest.MonkeyPatch):
 
 
 def test_qwen3_next_bf16_moe_flashinfer_trtllm(monkeypatch: pytest.MonkeyPatch):
-    monkeypatch.setenv("VLLM_USE_FLASHINFER_MOE_FP16", "1")
-    can_initialize("Qwen/Qwen3-Next-80B-A3B-Instruct", hf_overrides=HF_OVERRIDE_TEXT)
+    can_initialize(
+        "Qwen/Qwen3-Next-80B-A3B-Instruct",
+        hf_overrides=HF_OVERRIDE_TEXT,
+        extra_args=["--moe-backend=flashinfer_trtllm"],
+    )