diff --git a/include/mlir-hlo/Dialect/mhlo/IR/hlo_ops.td b/include/mlir-hlo/Dialect/mhlo/IR/hlo_ops.td
index 2e17834..ed62ef8 100644
--- a/include/mlir-hlo/Dialect/mhlo/IR/hlo_ops.td
+++ b/include/mlir-hlo/Dialect/mhlo/IR/hlo_ops.td
@@ -157,6 +157,9 @@ def HLO_AbsOp: HLO_UnaryElementwiseOp<"abs",
   >];
 }
 
+def HLO_CbrtOp: HLO_UnaryElementwiseOp<"cbrt",
+    [NoSideEffect, SameOperandsAndResultType], HLO_FpTensor>, BASE_HLO_CbrtOp;
+
 def HLO_CeilOp: HLO_UnaryElementwiseOp<"ceil",
     [NoSideEffect, SameOperandsAndResultType], HLO_FpTensor>, BASE_HLO_CeilOp;
 
@@ -1423,4 +1426,21 @@ def HLO_FusionOp : HLO_Op<"fusion", []> {
   let hasCustomHLOConverter = 1;
 }
 
+// This is an op for purposes internal to XLA/GPU.
+def HLO_BitcastOp : HLO_Op<"bitcast", [NoSideEffect]>, BASE_HLO_BitcastOp {
+  let arguments = (ins HLO_Tensor:$operand);
+  let results = (outs HLO_Tensor);
+  let hasCustomHLOConverter = 1;
+}
+
+def HLO_ReducePrecisionOp: HLO_Op<"reduce_precision", [SameOperandsAndResultShape]>,
+                           BASE_HLO_ReducePrecisionOp {
+  let arguments = (ins
+    HLO_FpTensor:$operand,
+    I32Attr:$exponent_bits,
+    I32Attr:$mantissa_bits
+  );
+  let results = (outs HLO_FpTensor:$output);
+}
+
 #endif // HLO_OPS
diff --git a/include/mlir-hlo/Dialect/mhlo/IR/hlo_ops_base.td b/include/mlir-hlo/Dialect/mhlo/IR/hlo_ops_base.td
index b8378fe..6386972 100644
--- a/include/mlir-hlo/Dialect/mhlo/IR/hlo_ops_base.td
+++ b/include/mlir-hlo/Dialect/mhlo/IR/hlo_ops_base.td
@@ -127,6 +127,17 @@ class BASE_HLO_AbsOp {
   }];
 }
 
+class BASE_HLO_CbrtOp {
+  string summary = "Cubic root operator";
+
+  string description = [{
+    Returns element-wise cubic root of the operand.
+
+    See
+    https://www.tensorflow.org/xla/operation_semantics#element-wise_unary_functions.
+  }];
+}
+
 class BASE_HLO_CeilOp {
   string summary = "Ceil operator";
 
@@ -1336,4 +1347,17 @@ class BASE_HLO_WhileOp {
   }];
 }
 
+class BASE_HLO_BitcastOp {
+  string summary = "Bitcast operator";
+
+  string description = [{
+    This op changes the shape of the input in the way that the physical
+    arranggment of elements are unchanged.
+
+    However, the op needs layout information to make sense of "physical
+    arrangement of elements". Layout support in MHLO is currently under
+    exploration.
+  }];
+}
+
 #endif // HLO_OPS_BASE
diff --git a/tests/ops.mlir b/tests/ops.mlir
index 8cf8dba..4462d9c 100644
--- a/tests/ops.mlir
+++ b/tests/ops.mlir
@@ -1193,3 +1193,24 @@ func @incompatible_shapes(%arg0: tensor<?xf32>, %shape: tensor<2xindex>) -> tens
   %0 = "mhlo.dynamic_reshape"(%arg0, %shape) : (tensor<?xf32>, tensor<2xindex>) -> tensor<?xf32>
   return %0 : tensor<?xf32>
 }
+
+// -----
+
+func @cbrt(%arg: tensor<2x4xf32>) -> tensor<2x4xf32> {
+  %0 = "mhlo.cbrt"(%arg) : (tensor<2x4xf32>) -> tensor<2x4xf32>
+  return %0 : tensor<2x4xf32>
+}
+
+// -----
+
+func @bitcast(%arg: tensor<2x4xf32>) -> tensor<2x4xf32> {
+  %0 = "mhlo.bitcast"(%arg) : (tensor<2x4xf32>) -> tensor<2x4xf32>
+  return %0 : tensor<2x4xf32>
+}
+
+// -----
+
+func @bitcast(%arg: tensor<2x4xf32>) -> tensor<2x4xf32> {
+  %0 = "mhlo.reduce_precision"(%arg) {exponent_bits=2 : i32, mantissa_bits=3 : i32} : (tensor<2x4xf32>) -> tensor<2x4xf32>
+  return %0 : tensor<2x4xf32>
+}