diff --git a/vllm/model_executor/layers/fused_moe/experts/trtllm_fp8_moe.py b/vllm/model_executor/layers/fused_moe/experts/trtllm_fp8_moe.py
index febb3b2ef..183324420 100644
--- a/vllm/model_executor/layers/fused_moe/experts/trtllm_fp8_moe.py
+++ b/vllm/model_executor/layers/fused_moe/experts/trtllm_fp8_moe.py
@@ -240,12 +240,11 @@ class TrtLlmFp8Experts(mk.FusedMoEExpertsMonolithic):
     ) -> torch.Tensor:
         # Delay import for non-CUDA.
         import flashinfer
-        from flashinfer.fused_moe.core import ActivationType
 
         # Confirm supported activation function.
         assert activation in [MoEActivation.SILU, MoEActivation.RELU2_NO_MUL]
 
-        activation_type = ActivationType(activation_to_flashinfer_int(activation))
+        activation_type = activation_to_flashinfer_int(activation)
 
         # Confirm Llama-4 routing is proper.
         if self.routing_method_type == RoutingMethodType.Llama4:
diff --git a/vllm/model_executor/layers/fused_moe/experts/trtllm_nvfp4_moe.py b/vllm/model_executor/layers/fused_moe/experts/trtllm_nvfp4_moe.py
index 502671766..174c581b3 100644
--- a/vllm/model_executor/layers/fused_moe/experts/trtllm_nvfp4_moe.py
+++ b/vllm/model_executor/layers/fused_moe/experts/trtllm_nvfp4_moe.py
@@ -323,4 +323,5 @@ class TrtLlmNvFp4ExpertsMonolithic(
             routed_scaling_factor=routed_scaling_factor,
             routing_method_type=self.routing_method_type,
             do_finalize=True,
+            activation_type=activation_to_flashinfer_int(activation),
         )[0]