diff --git a/test/cpp/test_aten_xla_tensor_4.cpp b/test/cpp/test_aten_xla_tensor_4.cpp
index ff6130ca1b95..7a02a1079a6c 100644
--- a/test/cpp/test_aten_xla_tensor_4.cpp
+++ b/test/cpp/test_aten_xla_tensor_4.cpp
@@ -504,6 +504,19 @@ TEST_F(AtenXlaTensorTest, TestDivScalar) {
   ExpectCounterChanged("xla::div", cpp_test::GetIgnoredCounters());
 }
 
+TEST_F(AtenXlaTensorTest, TestDivScalarHalfOverflow) {
+  torch::Tensor input = torch::rand({3, 4}, torch::TensorOptions(torch::kHalf));
+  torch::Scalar other = torch::Scalar(100000);
+  torch::Tensor out = torch::div(input, other);
+  ForEachDevice([&](const torch::Device& device) {
+    torch::Tensor xla_input = CopyToDevice(input, device);
+    torch::Tensor xla_out = torch::div(xla_input, other);
+    AllClose(out, xla_out);
+  });
+  ExpectCounterNotChanged("aten::.*", cpp_test::GetIgnoredCounters());
+  ExpectCounterChanged("xla::div", cpp_test::GetIgnoredCounters());
+}
+
 TEST_F(AtenXlaTensorTest, TestDivScalarInPlace) {
   for (torch::ScalarType scalar_type : {torch::kFloat}) {
     torch::Tensor a =
diff --git a/torch_xla/csrc/tensor_methods.cpp b/torch_xla/csrc/tensor_methods.cpp
index bad4a7c6c2e1..7baa951c9a6e 100644
--- a/torch_xla/csrc/tensor_methods.cpp
+++ b/torch_xla/csrc/tensor_methods.cpp
@@ -1,5 +1,6 @@
 #include "torch_xla/csrc/tensor_methods.h"
 
+#include <ATen/OpMathType.h>
 #include <ATen/core/Reduction.h>
 #include <torch/csrc/autograd/variable.h>
 #include <torch/csrc/lazy/core/helpers.h>
@@ -1260,10 +1261,14 @@ XLATensorPtr div(const XLATensorPtr& input, const at::Scalar& other) {
   if (input_is_float) {
     scalar_type = MaybeUpcastToHostTorchType(input_type);
   }
-  torch::lazy::Value input_value = GetFloatingIrValue(input, scalar_type);
+  at::ScalarType op_math_type = at::toOpMathType(scalar_type);
+  torch::lazy::Value input_value =
+      torch::lazy::MakeNode<Cast>(input->GetIrValue(), op_math_type);
   torch::lazy::Value other_value = XLAGraphExecutor::Get()->GetIrValueForScalar(
-      other, GetXlaShape(input_value).element_type(), input->GetDevice());
-  return input->CreateFrom(Div(input_value, other_value), scalar_type);
+      other, XlaTypeFromTorchType(op_math_type), input->GetDevice());
+  return input->CreateFrom(
+      torch::lazy::MakeNode<Cast>(Div(input_value, other_value), scalar_type),
+      scalar_type);
 }
 
 XLATensorPtr einsum(const std::string& equation,