diff --git a/include/ck_tile/core/utility/reduce_operator.hpp b/include/ck_tile/core/utility/reduce_operator.hpp
index 2d7ac78b06..a698c91e45 100644
--- a/include/ck_tile/core/utility/reduce_operator.hpp
+++ b/include/ck_tile/core/utility/reduce_operator.hpp
@@ -35,8 +35,6 @@ struct Add
 
         return type_convert<T>(y_ + x_);
     }
-
-    static constexpr bool requires_special_combine = false;
 };
 
 struct SquareAdd
@@ -64,28 +62,6 @@ struct SquareAdd
         float x_ = type_convert<float>(x);
         return type_convert<T>(y_ + (x_ * x_));
     }
-
-    // For combining partial results
-    template <typename T,
-              typename = std::enable_if_t<std::is_same_v<T, float> || std::is_same_v<T, double> ||
-                                          std::is_same_v<T, int32_t> || std::is_same_v<T, int8_t>>>
-    CK_TILE_HOST_DEVICE constexpr T combine_partial_results(const T& partial1,
-                                                            const T& partial2) const
-    {
-        return partial1 + partial2; // Just add the partial sums, don't square again
-    }
-
-    template <typename T,
-              typename = std::enable_if_t<std::is_same_v<T, half_t> || std::is_same_v<T, bf16_t> ||
-                                          std::is_same_v<T, fp8_t> || std::is_same_v<T, bf8_t>>>
-    CK_TILE_HOST_DEVICE constexpr T combine_partial_results(T& partial1, T& partial2) const
-    {
-        float partial1_ = type_convert<float>(partial1);
-        float partial2_ = type_convert<float>(partial2);
-        return type_convert<T>(partial1_ + partial2_);
-    }
-
-    static constexpr bool requires_special_combine = true;
 };
 
 struct Max
@@ -109,8 +85,6 @@ struct Max
     {
         return max(y, x);
     }
-
-    static constexpr bool requires_special_combine = false;
 };
 
 struct AbsMax
@@ -134,8 +108,6 @@ struct AbsMax
     {
         return max(y, abs(x));
     }
-
-    static constexpr bool requires_special_combine = false;
 };
 
 } // namespace ReduceOp
diff --git a/include/ck_tile/ops/reduce/block/block_reduce2d.hpp b/include/ck_tile/ops/reduce/block/block_reduce2d.hpp
index 849fa6c252..b72657b785 100644
--- a/include/ck_tile/ops/reduce/block/block_reduce2d.hpp
+++ b/include/ck_tile/ops/reduce/block/block_reduce2d.hpp
@@ -183,16 +183,7 @@ struct BlockReduce2dSync
 
                         // pull data from remote lane
                         const auto v_remote = warp_shuffle(v_local, src_lane);
-
-                        // For reduce, use combine_partial_results for operations that require it
-                        if constexpr(ReduceFunc::requires_special_combine)
-                        {
-                            v_local = reduce_func.combine_partial_results(v_local, v_remote);
-                        }
-                        else
-                        {
-                            v_local = reduce_func(v_local, v_remote);
-                        }
+                        v_local             = reduce_func(v_local, v_remote);
                     });
                 }
             });
@@ -309,16 +300,7 @@ struct BlockReduce2dCrossWarpSync
             static_for<0, num_reduce_warps - 1, 1>{}([&](auto i_1_n1) {
                 constexpr auto i_1      = number<i_1_n1 + 1>{};
                 const DataType v_remote = all_scratch[i_0 * num_reduce_warps + i_1];
-
-                // For reduce, use combine_partial_results for operations that require it
-                if constexpr(ReduceFunc::requires_special_combine)
-                {
-                    v_local = reduce_func.combine_partial_results(v_local, v_remote);
-                }
-                else
-                {
-                    v_local = reduce_func(v_local, v_remote);
-                }
+                v_local                 = reduce_func(v_local, v_remote);
             });
 
             y_tensor.get_thread_buffer()(i_0) = v_local;
diff --git a/include/ck_tile/ops/reduce/kernel/reduce2d_kernel.hpp b/include/ck_tile/ops/reduce/kernel/reduce2d_kernel.hpp
index f65487ea6e..0cae4023b7 100644
--- a/include/ck_tile/ops/reduce/kernel/reduce2d_kernel.hpp
+++ b/include/ck_tile/ops/reduce/kernel/reduce2d_kernel.hpp
@@ -189,7 +189,9 @@ struct Reduce
     /// @note Requirements:
     ///       - y_continous_dim % ThreadTile_N == 0 (for proper thread distribution)
     ///       - input_strides[-1] == 1 (for contiguous memory access)
-    CK_TILE_HOST static bool IsSupportedArgument(index_t y_continous_dim, auto input_strides)
+    template <typename InputStrides>
+    CK_TILE_HOST static bool IsSupportedArgument(index_t y_continous_dim,
+                                                 InputStrides input_strides)
     {
         using S = typename Problem::BlockShape;
 
diff --git a/test/ck_tile/reduce/test_reduce2d.cpp b/test/ck_tile/reduce/test_reduce2d.cpp
index 4ce0b56ef3..821d0a6c3e 100644
--- a/test/ck_tile/reduce/test_reduce2d.cpp
+++ b/test/ck_tile/reduce/test_reduce2d.cpp
@@ -308,20 +308,8 @@ using TestConfig_F32_Max = std::tuple<float,
                                       Shape1_WarpTile,
                                       Shape1_ThreadTile>;
 
-using TestConfig_F32_SquareAdd = std::tuple<float,
-                                            float,
-                                            float,
-                                            ck_tile::ReduceOp::SquareAdd,
-                                            Shape1_BlockWarps,
-                                            Shape1_BlockTile,
-                                            Shape1_WarpTile,
-                                            Shape1_ThreadTile>;
-
-using TestTypes = ::testing::Types<TestConfig_F32_Add,
-                                   TestConfig_F16_Add,
-                                   TestConfig_F32_CrossWarp,
-                                   TestConfig_F32_Max,
-                                   TestConfig_F32_SquareAdd>;
+using TestTypes = ::testing::
+    Types<TestConfig_F32_Add, TestConfig_F16_Add, TestConfig_F32_CrossWarp, TestConfig_F32_Max>;
 
 TYPED_TEST_SUITE(TestCkTileReduce, TestTypes);