diff --git a/ttnn/cpp/ttnn/operations/eltwise/binary/binary.cpp b/ttnn/cpp/ttnn/operations/eltwise/binary/binary.cpp
index 8cbf4e001b64..b0020048eb11 100644
--- a/ttnn/cpp/ttnn/operations/eltwise/binary/binary.cpp
+++ b/ttnn/cpp/ttnn/operations/eltwise/binary/binary.cpp
@@ -108,28 +108,54 @@ auto preprocess_inputs(const Tensor &input_tensor_a_arg, const Tensor &input_ten
     Tensor input_tensor_a = input_tensor_a_arg;
     Tensor input_tensor_b = input_tensor_b_arg;
 
+    auto shape_a = input_tensor_a.get_shape();
+    auto shape_b = input_tensor_b.get_shape();
+    auto rank_a = shape_a.rank();
+    auto rank_b = shape_b.rank();
+
+    if(rank_a != rank_b){
+
+        auto max_rank = std::max(rank_a, rank_b);
+        auto min_rank = std::min(rank_a, rank_b);
+
+        // if(optional_output_tensor.has_value()) {
+        //     auto opt_rank = optional_output_tensor.value().get_shape().rank();
+        //     TT_FATAL( max_rank == opt_rank,
+        //     "Output Tensor rank {} doesn't match input tensor rank {}.", opt_rank, max_rank );
+        // }
+
+        std::vector<int32_t> shape_vector(max_rank, 1);
+        auto& reshaped_tensor = (rank_a > rank_b) ? input_tensor_b : input_tensor_a;
+        auto s_b = reshaped_tensor.get_shape();
+        for(int i=0; i < min_rank; ++i){
+            shape_vector[(max_rank - min_rank) + i] = s_b[i];
+        }
+        reshaped_tensor = ttnn::reshape(reshaped_tensor, shape_vector);
+
+    }
+
     // TODO: #7731 (Remove calls to repeat )
-    auto repeat_smaller = [](const auto &first, auto &second) {
+    auto repeat_smaller = [](const auto &first, auto &second, auto first_rank, auto second_rank) {
         const auto first_shape = first.get_shape();
         const auto second_shape = second.get_shape();
         // repeats second if it is smaller
-        if (first_shape.rank() == 4 and second_shape.rank() == 4 and first_shape[0] > second_shape[0]) {
+        if (first_rank == 4 and second_rank == 4 and first_shape[0] > second_shape[0]) {
             TT_FATAL(second_shape[0] == 1, "Dimension trying to broadcast is not equal to 1");
             Shape repeats(std::array<uint32_t, 4>{first_shape[0], 1, 1, 1});
             second = ttnn::repeat(second, repeats);
         }
         // repeats second if it is smaller
-        if (first_shape.rank() >= 3 and second_shape.rank() >= 3 and first_shape[-3] > second_shape[-3]) {
+        if (first_rank >= 3 and second_rank >= 3 and first_shape[-3] > second_shape[-3]) {
             TT_FATAL(second_shape[-3] == 1, "Dimension trying to broadcast is not equal to 1");
-            int rank_a = first_shape.rank();
+            int rank_a = first_rank;
             std::vector<uint32_t> repeat_dim(rank_a, 1);
             repeat_dim[rank_a - 3] = first_shape[rank_a - 3];
             Shape repeats(repeat_dim);
             second = ttnn::repeat(second, repeats);
         }
     };
-    repeat_smaller(input_tensor_a, input_tensor_b);
-    repeat_smaller(input_tensor_b, input_tensor_a);
+    repeat_smaller(input_tensor_a, input_tensor_b, rank_a, rank_b);
+    repeat_smaller(input_tensor_b, input_tensor_a, rank_b, rank_a);
 
     return [](const auto &input_tensor_a, const auto &input_tensor_b) {
         if constexpr (detail::is_associative(binary_op_type)) {