diff --git a/onnxruntime/test/perftest/ort_test_session.cc b/onnxruntime/test/perftest/ort_test_session.cc
index 9b15ebb394..04e9655340 100644
--- a/onnxruntime/test/perftest/ort_test_session.cc
+++ b/onnxruntime/test/perftest/ort_test_session.cc
@@ -1,4 +1,5 @@
 #include "ort_test_session.h"
+#include <algorithm>
 #include <set>
 #include <core/session/onnxruntime_cxx_api.h>
 #include "core/session/onnxruntime_session_options_config_keys.h"
@@ -386,7 +387,7 @@ OnnxRuntimeTestSession::OnnxRuntimeTestSession(Ort::Env& env, std::random_device
       if (key == "runtime") {
         std::set<std::string> supported_runtime = {"CPU", "GPU_FP32", "GPU", "GPU_FLOAT16", "DSP", "AIP_FIXED_TF"};
         if (supported_runtime.find(value) == supported_runtime.end()) {
-          ORT_THROW(R"(Wrong configuration value for the key 'runtime'. 
+          ORT_THROW(R"(Wrong configuration value for the key 'runtime'.
 select from 'CPU', 'GPU_FP32', 'GPU', 'GPU_FLOAT16', 'DSP', 'AIP_FIXED_TF'. \n)");
         }
       } else if (key == "priority") {
@@ -394,7 +395,7 @@ select from 'CPU', 'GPU_FP32', 'GPU', 'GPU_FLOAT16', 'DSP', 'AIP_FIXED_TF'. \n)"
       } else if (key == "buffer_type") {
         std::set<std::string> supported_buffer_type = {"TF8", "TF16", "UINT8", "FLOAT", "ITENSOR"};
         if (supported_buffer_type.find(value) == supported_buffer_type.end()) {
-          ORT_THROW(R"(Wrong configuration value for the key 'buffer_type'. 
+          ORT_THROW(R"(Wrong configuration value for the key 'buffer_type'.
 select from 'TF8', 'TF16', 'UINT8', 'FLOAT', 'ITENSOR'. \n)");
         }
       } else {
@@ -563,6 +564,47 @@ select from 'TF8', 'TF16', 'UINT8', 'FLOAT', 'ITENSOR'. \n)");
   }
 }
 
+template <typename T>
+static void FillTensorDataTyped(Ort::Value& tensor, size_t count, T value = T{}) {
+  T* data = tensor.GetTensorMutableData<T>();
+  std::fill_n(data, count, value);
+}
+
+static void InitializeTensorData(Ort::Value& tensor) {
+  const auto type_and_shape = tensor.GetTensorTypeAndShapeInfo();
+  const auto count = type_and_shape.GetElementCount();
+  const auto element_type = type_and_shape.GetElementType();
+
+#define CASE_FOR_TYPE(T)                   \
+  case Ort::TypeToTensorType<T>::type: {   \
+    FillTensorDataTyped<T>(tensor, count); \
+  } break
+
+  switch (element_type) {
+    CASE_FOR_TYPE(Ort::Float16_t);
+    CASE_FOR_TYPE(Ort::BFloat16_t);
+    CASE_FOR_TYPE(float);
+    CASE_FOR_TYPE(double);
+    CASE_FOR_TYPE(int8_t);
+    CASE_FOR_TYPE(int16_t);
+    CASE_FOR_TYPE(int32_t);
+    CASE_FOR_TYPE(int64_t);
+    CASE_FOR_TYPE(uint8_t);
+    CASE_FOR_TYPE(uint16_t);
+    CASE_FOR_TYPE(uint32_t);
+    CASE_FOR_TYPE(uint64_t);
+    CASE_FOR_TYPE(bool);
+    case ONNX_TENSOR_ELEMENT_DATA_TYPE_STRING:
+      // string tensors are already initialized to contain empty strings
+      // see onnxruntime::Tensor::Init()
+      break;
+    default:
+      ORT_THROW("Unsupported tensor data type: ", element_type);
+  }
+
+#undef CASE_FOR_TYPE
+}
+
 bool OnnxRuntimeTestSession::PopulateGeneratedInputTestData() {
   // iterate over all input nodes
   for (size_t i = 0; i < static_cast<size_t>(input_length_); i++) {
@@ -582,6 +624,7 @@ bool OnnxRuntimeTestSession::PopulateGeneratedInputTestData() {
       auto allocator = static_cast<OrtAllocator*>(Ort::AllocatorWithDefaultOptions());
       Ort::Value input_tensor = Ort::Value::CreateTensor(allocator, (const int64_t*)input_node_dim.data(),
                                                          input_node_dim.size(), tensor_info.GetElementType());
+      InitializeTensorData(input_tensor);
       PreLoadTestData(0, i, std::move(input_tensor));
     }
   }