diff --git a/core/conversion/converters/impl/reduce.cpp b/core/conversion/converters/impl/reduce.cpp
index b3db09ffd7..68d4c41fa5 100644
--- a/core/conversion/converters/impl/reduce.cpp
+++ b/core/conversion/converters/impl/reduce.cpp
@@ -72,6 +72,13 @@ auto reduce_registrations TORCHTRT_UNUSED =
                auto in_dims = util::toVec(in_tensor->getDimensions());
                LOG_WARNING("Sum Converter disregards dtype");
 
+               if (in_tensor->getType() == nvinfer1::DataType::kBOOL) {
+                 LOG_DEBUG(
+                     "Found type  " << in_tensor->getType() << " in aten::sum, casting to "
+                                    << nvinfer1::DataType::kINT32 << " for compatibility.");
+                 in_tensor = castITensor(ctx, in_tensor, nvinfer1::DataType::kINT32);
+               }
+
                uint32_t axis_mask = (uint32_t)(((uint64_t)1 << in_dims.size()) - 1);
 
                auto sum_layer = ctx->net->addReduce(*in_tensor, nvinfer1::ReduceOperation::kSUM, axis_mask, false);
diff --git a/tests/core/conversion/converters/test_reduce.cpp b/tests/core/conversion/converters/test_reduce.cpp
index 4699427d5e..3bcef3db77 100644
--- a/tests/core/conversion/converters/test_reduce.cpp
+++ b/tests/core/conversion/converters/test_reduce.cpp
@@ -137,6 +137,16 @@ converts_keepdims_correctly(mean, Mean);
 
 #undef converts_keepdims_correctly
 
+TEST(Converters, ATenSumBoolConvertsCorrectly) {
+  const auto graph = R"IR(
+    graph(%0 : Tensor):
+      %4 : None = prim::Constant()
+      %5 : Tensor = aten::sum(%0, %4)
+      return (%5))IR";
+  auto in = at::randint(-1, 2, {4, 4, 4}, at::kCUDA).to(at::kBool);
+  test_body(graph, in);
+}
+
 TEST(Converters, ATenSumDimNegOneIndexConvertsCorrectly) {
   const auto graph = R"IR(
     graph(%0 : Tensor):