diff --git a/mlir/lib/Dialect/Linalg/Transforms/Vectorization.cpp b/mlir/lib/Dialect/Linalg/Transforms/Vectorization.cpp
--- a/mlir/lib/Dialect/Linalg/Transforms/Vectorization.cpp
+++ b/mlir/lib/Dialect/Linalg/Transforms/Vectorization.cpp
@@ -1015,6 +1015,7 @@
 ///   (Implies that sizes of `insertOp` are all static.)
 /// - Only unit strides in `insertOp`.
 /// - Single, scalar padding value.
+/// - `padOp` result not used as destination.
 struct PadTensorOpVectorizationWithInsertSlicePattern
     : public VectorizePadTensorOpUserPattern<tensor::InsertSliceOp> {
   using VectorizePadTensorOpUserPattern<
@@ -1035,6 +1036,9 @@
     // Dynamic shapes not supported.
     if (!padOp.result().getType().cast<ShapedType>().hasStaticShape())
       return failure();
+    // Pad result not used as destination.
+    if (insertOp.dest() == padOp.result())
+      return failure();
 
     auto vecType = VectorType::get(padOp.getType().getShape(),
                                    padOp.getType().getElementType());
diff --git a/mlir/test/Dialect/Linalg/vectorization.mlir b/mlir/test/Dialect/Linalg/vectorization.mlir
--- a/mlir/test/Dialect/Linalg/vectorization.mlir
+++ b/mlir/test/Dialect/Linalg/vectorization.mlir
@@ -684,7 +684,7 @@
 
 func private @make_vector() -> tensor<12x13xf32>
 
-// CHECK-LABEL: func @pad_and_insert_slice
+// CHECK-LABEL: func @pad_and_insert_slice_source
 //  CHECK-SAME:     %[[ARG0:.*]]: tensor<5x6xf32>
 //   CHECK-NOT:   linalg.pad_tensor
 //   CHECK-DAG:   %[[C0:.*]] = arith.constant 0 : index
@@ -693,7 +693,7 @@
 //       CHECK:   %[[READ:.*]] = vector.transfer_read %[[ARG0]][%[[C0]], %[[C0]]], %[[C5]] : tensor<5x6xf32>, vector<7x9xf32>
 //       CHECK:   %[[WRITE:.*]] = vector.transfer_write %[[READ]], %[[VEC0]][%[[C0]], %[[C0]]] {in_bounds = [true, true]} : vector<7x9xf32>, tensor<12x13xf32>
 //       CHECK:   return %[[WRITE]]
-func @pad_and_insert_slice(
+func @pad_and_insert_slice_source(
     %arg0: tensor<5x6xf32>) -> tensor<12x13xf32> {
   %c0 = arith.constant 0 : index
   %c5 = arith.constant 5.0 : f32
@@ -708,6 +708,26 @@
 
 // -----
 
+func private @make_vector() -> tensor<12x13xf32>
+
+// CHECK-LABEL: func @pad_and_insert_slice_dest
+// Check the insert slice is not rewritten if the padded result is used by the destination operand.
+//       CHECK:   %[[T1:.*]] = call @make_vector() : () -> tensor<12x13xf32>
+//       CHECK:   = tensor.insert_slice %[[T1]] into
+func @pad_and_insert_slice_dest(
+    %arg0: tensor<1x5x6xf32>) -> tensor<1x12x13xf32> {
+  %c5 = arith.constant 5.0 : f32
+  %0 = linalg.pad_tensor %arg0 low[0, 0, 0] high[0, 7, 7] {
+    ^bb0(%arg2: index, %arg3: index, %arg4: index):
+      linalg.yield %c5 : f32
+  } : tensor<1x5x6xf32> to tensor<1x12x13xf32>
+  %1 = call @make_vector() : () -> tensor<12x13xf32>
+  %r = tensor.insert_slice %1 into %0[0, 0, 0][1, 12, 13][1, 1, 1] : tensor<12x13xf32> into tensor<1x12x13xf32>
+  return %r : tensor<1x12x13xf32>
+}
+
+// -----
+
 // CHECK-LABEL: func @pad_tensor_non_const_pad_value
 //  CHECK-SAME:     %[[ARG0:.*]]: tensor<5x6xf32>
 //   CHECK-NOT:   linalg.pad_tensor