diff --git a/tests/ExecuteNetwork/ArmNNExecutor.cpp b/tests/ExecuteNetwork/ArmNNExecutor.cpp
index 730c072..29ef4c5 100644
--- a/tests/ExecuteNetwork/ArmNNExecutor.cpp
+++ b/tests/ExecuteNetwork/ArmNNExecutor.cpp
@@ -707,48 +707,14 @@
 void ArmNNExecutor::CompareAndPrintResult(std::vector<const void*> otherOutput)
 {
     unsigned int index = 0;
-
+    std::string typeString;
     for (const auto& outputTensors: m_OutputTensorsVec)
     {
         for (const auto& outputTensor: outputTensors)
         {
-            float result = 0;
             size_t size = outputTensor.second.GetNumBytes();
-
-            switch (outputTensor.second.GetDataType())
-            {
-                case armnn::DataType::Float32:
-                {
-                    result = ComputeRMSE<float>(outputTensor.second.GetMemoryArea(), otherOutput[index++], size);
-                    break;
-                }
-                case armnn::DataType::Signed32:
-                {
-                    result = ComputeRMSE<int32_t>(outputTensor.second.GetMemoryArea(), otherOutput[index++], size);
-                    break;
-                }
-                case armnn::DataType::QSymmS16:
-                {
-                    result = ComputeRMSE<int16_t>(outputTensor.second.GetMemoryArea(), otherOutput[index++], size);
-                    break;
-                }
-                case armnn::DataType::QSymmS8:
-                case armnn::DataType::QAsymmS8:
-                {
-                    result = ComputeRMSE<int8_t>(outputTensor.second.GetMemoryArea(), otherOutput[index++], size);
-                    break;
-                }
-                case armnn::DataType::QAsymmU8:
-                {
-                    result = ComputeRMSE<uint8_t>(outputTensor.second.GetMemoryArea(), otherOutput[index++], size);
-                    break;
-                }
-                default:
-                {
-                    LogAndThrow("Unexpected DataType");
-                }
-            }
-            std::cout << "RMSE: of " << result << "\n";
+            double result = ComputeByteLevelRMSE(outputTensor.second.GetMemoryArea(), otherOutput[index++], size);
+            std::cout << "Byte level root mean square error: " << result << "\n";
         }
     }
 }
diff --git a/tests/ExecuteNetwork/ExecuteNetworkProgramOptions.cpp b/tests/ExecuteNetwork/ExecuteNetworkProgramOptions.cpp
index cba6748..007f818 100644
--- a/tests/ExecuteNetwork/ExecuteNetworkProgramOptions.cpp
+++ b/tests/ExecuteNetwork/ExecuteNetworkProgramOptions.cpp
@@ -359,17 +359,19 @@
                  cxxopts::value<std::string>()->default_value("parser"))
 
                 ("C, compare-output",
-                 "Compare the output of the network with an output file that has been previously "
-                 "produced by running a network through ExecuteNetwork. See --write-outputs-to-file "
-                 "to produce an output file for an execution.",
+                 "Perform a per byte root mean square error calculation of the inference output with an output"
+                 " file that has been previously produced by running a network through ExecuteNetwork."
+                 " See --write-outputs-to-file to produce an output file for an execution.",
                  cxxopts::value<std::string>(m_ExNetParams.m_ComparisonFile))
 
                 ("B, compare-output-with-backend",
-                 "Compare the output of the network with a different backend.",
+                 "Perform a per byte root mean square error calculation of the output of the inference with a"
+                 " different backend.",
                  cxxopts::value<std::vector<std::string>>())
 
                 ("A, compare-with-tflite",
-                 "Compare the output of the network with the tflite ref model.",
+                 "Perform an per byte root mean square error calculation of the output of the inference with"
+                 " the tflite ref model.",
                  cxxopts::value<bool>(m_ExNetParams.m_CompareWithTflite)->default_value("false")
                          ->implicit_value("true"));
 
diff --git a/tests/ExecuteNetwork/TfliteExecutor.cpp b/tests/ExecuteNetwork/TfliteExecutor.cpp
index fc9c21a..f365623 100644
--- a/tests/ExecuteNetwork/TfliteExecutor.cpp
+++ b/tests/ExecuteNetwork/TfliteExecutor.cpp
@@ -230,45 +230,9 @@
     for (unsigned int outputIndex = 0; outputIndex < m_TfLiteInterpreter->outputs().size(); ++outputIndex)
     {
         auto tfLiteDelegateOutputId = m_TfLiteInterpreter->outputs()[outputIndex];
-        float result = 0;
-        switch (m_TfLiteInterpreter->tensor(tfLiteDelegateOutputId)->type)
-        {
-            case kTfLiteFloat32:
-            {
-                result =  ComputeRMSE<float>(m_TfLiteInterpreter->tensor(tfLiteDelegateOutputId)->allocation,
-                                             otherOutput[outputIndex],
-                                             m_TfLiteInterpreter->tensor(tfLiteDelegateOutputId)->bytes);
-
-                break;
-            }
-            case kTfLiteInt32:
-            {
-                result =  ComputeRMSE<int32_t>(m_TfLiteInterpreter->tensor(tfLiteDelegateOutputId)->allocation,
-                                                    otherOutput[outputIndex],
-                                                    m_TfLiteInterpreter->tensor(tfLiteDelegateOutputId)->bytes);
-                break;
-            }
-            case kTfLiteUInt8:
-            {
-                result =  ComputeRMSE<uint8_t>(m_TfLiteInterpreter->tensor(tfLiteDelegateOutputId)->allocation,
-                                                    otherOutput[outputIndex],
-                                                    m_TfLiteInterpreter->tensor(tfLiteDelegateOutputId)->bytes);
-                break;
-            }
-            case kTfLiteInt8:
-            {
-                result =  ComputeRMSE<int8_t>(m_TfLiteInterpreter->tensor(tfLiteDelegateOutputId)->allocation,
-                                                    otherOutput[outputIndex],
-                                                    m_TfLiteInterpreter->tensor(tfLiteDelegateOutputId)->bytes);
-                break;
-            }
-            default:
-            {
-            }
-        }
-
-        std::cout << "RMSE of "
-                  << m_TfLiteInterpreter->tensor(tfLiteDelegateOutputId)->name
-                  << ": " << result << std::endl;
+        size_t size = m_TfLiteInterpreter->tensor(tfLiteDelegateOutputId)->bytes;
+        double result = ComputeByteLevelRMSE(m_TfLiteInterpreter->tensor(tfLiteDelegateOutputId)->allocation,
+                                             otherOutput[outputIndex], size);
+        std::cout << "Byte level root mean square error: " << result << "\n";
     }
 };