diff --git a/tensorrt_llm/_torch/custom_ops/cute_dsl_custom_ops.py b/tensorrt_llm/_torch/custom_ops/cute_dsl_custom_ops.py
index ee7a2763f7d..1c9695b4e84 100644
--- a/tensorrt_llm/_torch/custom_ops/cute_dsl_custom_ops.py
+++ b/tensorrt_llm/_torch/custom_ops/cute_dsl_custom_ops.py
@@ -54,7 +54,6 @@ def __init__(self, alpha: float, output_dtype: torch.dtype):
                     f"SM version {get_sm_version()} is not supported for {self.__class__.__name__}, it only supports SM 100"
                 )
 
-        # rewrite the hash function because the value of self.alpha doesn't affect the tactic.
         def unique_id(self):
             return (self.output_dtype, )
 
@@ -531,6 +530,17 @@ def __init__(self,
                     f"SM version {get_sm_version()} is not supported for {self.__class__.__name__}, it only supports SM 100"
                 )
 
+        def unique_id(self):
+            return (
+                self.num_experts,
+                self.top_k,
+                self.num_local_experts,
+                self.local_expert_offset,
+                self.tile_size,
+                self.output_dtype,
+                self.scaling_vector_size,
+            )
+
         def get_valid_tactics(
             self,
             inputs: List[torch.Tensor],
@@ -571,7 +581,7 @@ def get_valid_tactics(
             return valid_tactics
 
         def get_tuning_config(self) -> TuningConfig:
-            key = hash(self)
+            key = self.unique_id()
             if key not in self.__class__.tuning_config_cache:
                 helper = GroupedGemmInputsHelper(self.num_experts, self.top_k,
                                                  self.num_local_experts,
@@ -807,6 +817,17 @@ def __init__(self,
                     f"SM version {get_sm_version()} is not supported for {self.__class__.__name__}, it only supports SM 100"
                 )
 
+        def unique_id(self):
+            return (
+                self.num_experts,
+                self.top_k,
+                self.num_local_experts,
+                self.local_expert_offset,
+                self.tile_size,
+                self.output_dtype,
+                self.scaling_vector_size,
+            )
+
         def get_valid_tactics(
             self,
             inputs: List[torch.Tensor],
@@ -847,7 +868,7 @@ def get_valid_tactics(
             return valid_tactics
 
         def get_tuning_config(self) -> TuningConfig:
-            key = hash(self)
+            key = self.unique_id()
             if key not in self.__class__.tuning_config_cache:
                 helper = GroupedGemmInputsHelper(self.num_experts, self.top_k,
                                                  self.num_local_experts,
@@ -1124,6 +1145,16 @@ def __init__(self,
                     f"SM version {get_sm_version()} is not supported for {self.__class__.__name__}, it only supports SM 100"
                 )
 
+        def unique_id(self):
+            return (
+                self.num_experts,
+                self.top_k,
+                self.num_local_experts,
+                self.local_expert_offset,
+                self.tile_size,
+                self.scaling_vector_size,
+            )
+
         def get_valid_tactics(
             self,
             inputs: List[torch.Tensor],
@@ -1164,7 +1195,7 @@ def get_valid_tactics(
             return valid_tactics
 
         def get_tuning_config(self) -> TuningConfig:
-            key = hash(self)
+            key = self.unique_id()
             if key not in self.__class__.tuning_config_cache:
                 helper = GroupedGemmInputsHelper(self.num_experts, self.top_k,
                                                  self.num_local_experts,
@@ -1443,6 +1474,16 @@ def __init__(self,
             self.output_dtype = output_dtype
             self.scaling_vector_size = scaling_vector_size
 
+        def unique_id(self):
+            return (
+                self.num_experts,
+                self.top_k,
+                self.num_local_experts,
+                self.local_expert_offset,
+                self.output_dtype,
+                self.scaling_vector_size,
+            )
+
         def get_valid_tactics(
             self,
             inputs: List[torch.Tensor],
@@ -1452,7 +1493,7 @@ def get_valid_tactics(
             return [128]
 
         def get_tuning_config(self) -> TuningConfig:
-            key = hash(self)
+            key = self.unique_id()
             if key not in self.__class__.tuning_config_cache:
                 helper = FusedMoEInputsHelper(self.num_experts, self.top_k,
                                               self.num_local_experts,