diff --git a/example/65_gemm_multiply_multiply/moe_gemm2.cpp b/example/65_gemm_multiply_multiply/moe_gemm2.cpp
index af67f8efd1..80a5484cdc 100644
--- a/example/65_gemm_multiply_multiply/moe_gemm2.cpp
+++ b/example/65_gemm_multiply_multiply/moe_gemm2.cpp
@@ -236,7 +236,7 @@ int main(int argc, char* argv[])
 
 
     // const ck::index_t experts = 8;
-    Tensor<ck::index_t> expert_ids(HostTensorDescriptor({experts}, {1}));
+    Tensor<ck::index_t> expert_ids(HostTensorDescriptor({sorted_tile_num}, {1}));
     Tensor<ck::index_t> sorted_token_ids(HostTensorDescriptor({sorted_size}, {1}));
     Tensor<ck::index_t> max_token_id(HostTensorDescriptor({1}));
     max_token_id.mData[0] = valid_size;
diff --git a/include/ck/tensor_operation/gpu/grid/gridwise_moe_gemm_scatter.hpp b/include/ck/tensor_operation/gpu/grid/gridwise_moe_gemm_scatter.hpp
index cd4cfd3b18..63042ae505 100644
--- a/include/ck/tensor_operation/gpu/grid/gridwise_moe_gemm_scatter.hpp
+++ b/include/ck/tensor_operation/gpu/grid/gridwise_moe_gemm_scatter.hpp
@@ -197,8 +197,11 @@ struct GridwiseMoeGemmScatter
 
     __host__ static auto CalculateGridSize(index_t M, index_t N)
     {
-        return std::make_tuple(math::integer_divide_ceil(N, NPerBlock),
-                               math::integer_divide_ceil(M, MPerBlock),
+        // return std::make_tuple(math::integer_divide_ceil(N, NPerBlock),
+        //                        math::integer_divide_ceil(M, MPerBlock),
+        //                        1);
+        return std::make_tuple(math::integer_divide_ceil(N, NPerBlock) * math::integer_divide_ceil(M, MPerBlock),
+                               1,
                                1);
     }
 
@@ -1149,10 +1152,22 @@ struct GridwiseMoeGemmScatter
             MakeCGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(
                 c_grid_desc_m_n, problem.MBlock, problem.NBlock);
 
-        const index_t block_n_id = __builtin_amdgcn_readfirstlane(blockIdx.x);
-        const index_t block_m_id = __builtin_amdgcn_readfirstlane(blockIdx.y);
-        const index_t expert_id = __builtin_amdgcn_readfirstlane(p_sorted_expert_ids[block_m_id]);
+
         const index_t max_token_id = __builtin_amdgcn_readfirstlane(p_max_token_id[0]);     
+        const index_t expert_block_id = blockIdx.x / problem.NBlock;
+        // const index_t b_block_id = blockIdx.x % problem.NBlock;
+        const index_t expert_id = __builtin_amdgcn_readfirstlane(p_sorted_expert_ids[expert_block_id]);
+        const index_t es = __builtin_amdgcn_readfirstlane(p_max_token_id[expert_block_id + 1]);
+        const index_t expert_swizzle = es > 0 ? es : 1; //p_max_token_id[expert_id + 1];
+        const index_t expert_block_swizzle = expert_block_id / expert_swizzle;
+        const index_t b_block_id_swizzle = blockIdx.x % (problem.NBlock * expert_swizzle);
+        const index_t block_n_id = __builtin_amdgcn_readfirstlane(b_block_id_swizzle % 8 +  b_block_id_swizzle / (8 * expert_swizzle) * 8);
+        const index_t block_m_id = __builtin_amdgcn_readfirstlane(expert_block_swizzle * expert_swizzle + b_block_id_swizzle / 8 % expert_swizzle);
+
+        // const index_t block_n_id = __builtin_amdgcn_readfirstlane(blockIdx.x);
+        // const index_t block_m_id = __builtin_amdgcn_readfirstlane(blockIdx.y);
+        // const index_t expert_id = __builtin_amdgcn_readfirstlane(p_sorted_expert_ids[block_m_id]);
+        // const index_t max_token_id = __builtin_amdgcn_readfirstlane(p_max_token_id[0]);     
         const index_t token0 = __builtin_amdgcn_readfirstlane(p_sorted_token_ids[block_m_id * MPerBlock] & 0xffffff);
         
         // constexpr auto M0 = ABlockTransferThreadClusterLengths_AK0_M_AK1{}.At(I1);