diff --git a/include/mlir-hlo/Dialect/mhlo/IR/hlo_ops.td b/include/mlir-hlo/Dialect/mhlo/IR/hlo_ops.td
index d0abbe0..12b9f5a 100644
--- a/include/mlir-hlo/Dialect/mhlo/IR/hlo_ops.td
+++ b/include/mlir-hlo/Dialect/mhlo/IR/hlo_ops.td
@@ -1079,6 +1079,8 @@ def HLO_GetDimensionSizeOp: HLO_Op<"get_dimension_size", [NoSideEffect]>,
   // XLA semantics is available. This limitation is because of the current XLA
   // implementation.
   let results = (outs I32Tensor);
+
+  let hasFolder = 1;
 }
 
 def HLO_MapOp: HLO_Op<"map",
diff --git a/lib/Dialect/mhlo/IR/hlo_ops.cc b/lib/Dialect/mhlo/IR/hlo_ops.cc
index f5deb94..b0fa4ce 100644
--- a/lib/Dialect/mhlo/IR/hlo_ops.cc
+++ b/lib/Dialect/mhlo/IR/hlo_ops.cc
@@ -165,6 +165,20 @@ static LogicalResult Verify(DotGeneralOp op) {
   return success();
 }
 
+//===----------------------------------------------------------------------===//
+// GetDimensionSizeOp
+//===----------------------------------------------------------------------===//
+
+/// Fold get_dimension_size when the said shape dimension is a constant.
+OpFoldResult GetDimensionSizeOp::fold(ArrayRef<Attribute> attrs) {
+  RankedTensorType type = operand().getType().cast<RankedTensorType>();
+  int32_t dim = dimension().getSExtValue();
+  if (type.isDynamic(dim)) return {};
+  // The result type is always is a 0-d i32 tensor.
+  return DenseIntElementsAttr::get<int32_t>(
+      getResult().getType().cast<RankedTensorType>(), type.getDimSize(dim));
+}
+
 //===----------------------------------------------------------------------===//
 // IotaOp
 //===----------------------------------------------------------------------===//
diff --git a/tests/canonicalize.mlir b/tests/canonicalize.mlir
index 0d20c3f..0b6cc1c 100644
--- a/tests/canonicalize.mlir
+++ b/tests/canonicalize.mlir
@@ -618,3 +618,11 @@ func @erase_dead_lhlo_constant_negative(%M : memref<4xf32>) -> memref<256x1024xf
   "lmhlo.constant"(%N) {value = dense<0.0> : tensor<f32>} : (memref<256x1024xf32>) -> ()
   return %N : memref<256x1024xf32>
 }
+
+// CHECK-LABEL: func @fold_get_dimension_size
+func @fold_get_dimension_size(%I : tensor<1x128x512xf32>) -> tensor<i32> {
+  %size = "mhlo.get_dimension_size"(%I) {dimension = 2 : i32} : (tensor<1x128x512xf32>) -> tensor<i32>
+  return %size : tensor<i32>
+  // CHECK-NEXT: %[[C:.*]] = mhlo.constant dense<512> : tensor<i32>
+  // CHECK-NEXT: return %[[C]]
+}