diff --git a/ttnn/cpp/ttnn/operations/matmul/device/matmul_op.cpp b/ttnn/cpp/ttnn/operations/matmul/device/matmul_op.cpp
index c17c0018039c..9b667bd401a3 100644
--- a/ttnn/cpp/ttnn/operations/matmul/device/matmul_op.cpp
+++ b/ttnn/cpp/ttnn/operations/matmul/device/matmul_op.cpp
@@ -371,7 +371,8 @@ inline MatmulProgramConfig create_simple_matmul_program_config(
 
     if (num_blocks_x * num_blocks_y <= num_cores_x * num_cores_y and Kt % in0_block_w == 0) {
         CoreCoord core_range = get_core_range(num_blocks_y, num_blocks_x, num_cores_y, num_cores_x);
-        if (core_range.y == 1 or (mem_config.is_sharded() and core_range.y == 0)) {
+        bool use_mcast_config = mem_config.is_sharded() and core_range.y == 0;
+        if (core_range.y == 1 or (use_mcast_config and mem_config.memory_layout == TensorMemoryLayout::WIDTH_SHARDED)) {
             return get_mcast_1d_config(
                 input_tensor_a,
                 input_tensor_b,
@@ -381,7 +382,7 @@ inline MatmulProgramConfig create_simple_matmul_program_config(
                 false /* out_sharded */,
                 std::nullopt /* compute_with_storage_grid_size */,
                 compute_kernel_config);
-        } else if (core_range.x == 1) {
+        } else if (core_range.x == 1 or (use_mcast_config and mem_config.memory_layout == TensorMemoryLayout::HEIGHT_SHARDED)) {
             return get_mcast_1d_config(
                 input_tensor_a,
                 input_tensor_b,
@@ -391,7 +392,8 @@ inline MatmulProgramConfig create_simple_matmul_program_config(
                 false /* out_sharded */,
                 std::nullopt /* compute_with_storage_grid_size */,
                 compute_kernel_config);
-        } else if (core_range.y > 0 && num_blocks_x <= num_cores_x && num_blocks_y <= num_cores_y) {
+        } else if ((core_range.y > 0 and num_blocks_x <= num_cores_x and num_blocks_y <= num_cores_y) or
+                (use_mcast_config and mem_config.memory_layout == TensorMemoryLayout::BLOCK_SHARDED)) {
             bool transpose_mcast = input_tensor_a.memory_config().memory_layout == TensorMemoryLayout::BLOCK_SHARDED &&
                                    input_tensor_a.shard_spec().value().orientation == ShardOrientation::COL_MAJOR;
             out_subblock_h = 4;