diff --git a/tensorflow/lite/kernels/broadcast_to_test.cc b/tensorflow/lite/kernels/broadcast_to_test.cc
index a36ed352055..9a352df62f0 100644
--- a/tensorflow/lite/kernels/broadcast_to_test.cc
+++ b/tensorflow/lite/kernels/broadcast_to_test.cc
@@ -214,6 +214,47 @@ TYPED_TEST(BroadcastToOpTest, ComplexBroadcast6DDynamicTest) {
                                 7, 8, 7, 8, 9, 10, 9, 10, 11, 12, 11, 12}));
 }
 
+TYPED_TEST(BroadcastToOpTest, ComplexBroadcast8DConstTest) {
+  BroadcastToOpModel<TypeParam> m({1, 3, 1, 2, 1, 4, 1, 1}, {8},
+                                  {2, 3, 1, 2, 2, 4, 1, 1});
+  m.SetInput({1,  2,  3,  4,  5,  6,  7,  8,  9,  10, 11, 12,
+              13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24});
+  m.Invoke();
+  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({2, 3, 1, 2, 2, 4, 1, 1}));
+  EXPECT_THAT(
+      m.GetOutput(),
+      ElementsAreArray({1,  2,  3,  4,  1,  2,  3,  4,  5,  6,  7,  8,  5,  6,
+                        7,  8,  9,  10, 11, 12, 9,  10, 11, 12, 13, 14, 15, 16,
+                        13, 14, 15, 16, 17, 18, 19, 20, 17, 18, 19, 20, 21, 22,
+                        23, 24, 21, 22, 23, 24, 1,  2,  3,  4,  1,  2,  3,  4,
+                        5,  6,  7,  8,  5,  6,  7,  8,  9,  10, 11, 12, 9,  10,
+                        11, 12, 13, 14, 15, 16, 13, 14, 15, 16, 17, 18, 19, 20,
+                        17, 18, 19, 20, 21, 22, 23, 24, 21, 22, 23, 24}));
+}
+
+TYPED_TEST(BroadcastToOpTest, ComplexBroadcast8DDynamicTest) {
+  BroadcastToOpModel<TypeParam> m({2, 1, 1, 2, 1, 4, 1, 1}, {8});
+  m.SetInput({1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16});
+  m.SetShape({2, 3, 2, 2, 2, 4, 1, 1});
+  m.Invoke();
+  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({2, 3, 2, 2, 2, 4, 1, 1}));
+  EXPECT_THAT(
+      m.GetOutput(),
+      ElementsAreArray(
+          {1, 2,  3,  4,  1, 2,  3,  4,  5,  6,  7,  8,  5,  6,  7,  8,
+           1, 2,  3,  4,  1, 2,  3,  4,  5,  6,  7,  8,  5,  6,  7,  8,
+           1, 2,  3,  4,  1, 2,  3,  4,  5,  6,  7,  8,  5,  6,  7,  8,
+           1, 2,  3,  4,  1, 2,  3,  4,  5,  6,  7,  8,  5,  6,  7,  8,
+           1, 2,  3,  4,  1, 2,  3,  4,  5,  6,  7,  8,  5,  6,  7,  8,
+           1, 2,  3,  4,  1, 2,  3,  4,  5,  6,  7,  8,  5,  6,  7,  8,
+           9, 10, 11, 12, 9, 10, 11, 12, 13, 14, 15, 16, 13, 14, 15, 16,
+           9, 10, 11, 12, 9, 10, 11, 12, 13, 14, 15, 16, 13, 14, 15, 16,
+           9, 10, 11, 12, 9, 10, 11, 12, 13, 14, 15, 16, 13, 14, 15, 16,
+           9, 10, 11, 12, 9, 10, 11, 12, 13, 14, 15, 16, 13, 14, 15, 16,
+           9, 10, 11, 12, 9, 10, 11, 12, 13, 14, 15, 16, 13, 14, 15, 16,
+           9, 10, 11, 12, 9, 10, 11, 12, 13, 14, 15, 16, 13, 14, 15, 16}));
+}
+
 TYPED_TEST(BroadcastToOpTest, ExtendingShape4DConstTest) {
   BroadcastToOpModel<TypeParam> m({3, 1, 2}, {4}, {3, 3, 2, 2});
   m.SetInput({1, 2, 3, 4, 5, 6});
@@ -233,6 +274,15 @@ TYPED_TEST(BroadcastToOpTest, NoBroadcastingConstTest) {
   EXPECT_THAT(m.GetOutput(), ElementsAreArray({1, 2, 3, 4, 5, 6}));
 }
 
+TYPED_TEST(BroadcastToOpTest, NoBroadcasting8DConstTest) {
+  BroadcastToOpModel<TypeParam> m({3, 1, 1, 1, 1, 1, 1, 2}, {8},
+                                  {3, 1, 1, 1, 1, 1, 1, 2});
+  m.SetInput({1, 2, 3, 4, 5, 6});
+  m.Invoke();
+  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({3, 1, 1, 1, 1, 1, 1, 2}));
+  EXPECT_THAT(m.GetOutput(), ElementsAreArray({1, 2, 3, 4, 5, 6}));
+}
+
 TYPED_TEST(BroadcastToOpTest, Int64ShapeConstTest) {
   BroadcastToOpModel<TypeParam, int64_t> m({1, 1, 1, 1, 1, 1, 2, 1}, {8},
                                            {1, 1, 1, 1, 1, 1, 2, 2});
diff --git a/tensorflow/lite/kernels/internal/reference/broadcast_to.h b/tensorflow/lite/kernels/internal/reference/broadcast_to.h
index 09ffa704cca..f106b2b52f6 100644
--- a/tensorflow/lite/kernels/internal/reference/broadcast_to.h
+++ b/tensorflow/lite/kernels/internal/reference/broadcast_to.h
@@ -72,14 +72,21 @@ inline void BroadcastTo(const RuntimeShape& unextended_input_shape,
 
   // Get the last dimension has broadcasting. At this dimension, the data is
   // copied from input tensor to output tensor.
-  int last_broadcast_dim = 0;
-  for (int i = N - 1; i > 0; --i) {
+  int last_broadcast_dim = -1;
+  for (int i = N - 1; i >= 0; --i) {
     if (input_desc.extents[i] != output_desc.extents[i]) {
       last_broadcast_dim = i;
       break;
     }
   }
 
+  // If non-broadcasting, just copy data from input to output tensor.
+  if (last_broadcast_dim == -1) {
+    memcpy(output_data, input_data,
+           unextended_input_shape.FlatSize() * TfLiteTypeGetSize(data_type));
+    return;
+  }
+
   // Broadcasting using memcpy.
   int indexes[N] = {0};
   BroadcastImpl<N>(input_desc, input_data, output_desc, output_data, indexes, 0,