diff --git a/delegate/test/ComparisonTestHelper.hpp b/delegate/test/ComparisonTestHelper.hpp
new file mode 100644
index 0000000..ef9f87a
--- /dev/null
+++ b/delegate/test/ComparisonTestHelper.hpp
@@ -0,0 +1,238 @@
+//
+// Copyright © 2020, 2023 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#pragma once
+
+#include "TestUtils.hpp"
+
+#include <armnn_delegate.hpp>
+
+#include <flatbuffers/flatbuffers.h>
+#include <tensorflow/lite/interpreter.h>
+#include <tensorflow/lite/kernels/register.h>
+#include <tensorflow/lite/model.h>
+#include <schema_generated.h>
+#include <tensorflow/lite/version.h>
+
+#include <doctest/doctest.h>
+
+namespace
+{
+
+std::vector<char> CreateComparisonTfLiteModel(tflite::BuiltinOperator comparisonOperatorCode,
+                                              tflite::TensorType tensorType,
+                                              const std::vector <int32_t>& input0TensorShape,
+                                              const std::vector <int32_t>& input1TensorShape,
+                                              const std::vector <int32_t>& outputTensorShape,
+                                              float quantScale = 1.0f,
+                                              int quantOffset  = 0)
+{
+    using namespace tflite;
+    flatbuffers::FlatBufferBuilder flatBufferBuilder;
+
+    std::vector<flatbuffers::Offset<tflite::Buffer>> buffers;
+    buffers.push_back(CreateBuffer(flatBufferBuilder));
+    buffers.push_back(CreateBuffer(flatBufferBuilder));
+    buffers.push_back(CreateBuffer(flatBufferBuilder));
+    buffers.push_back(CreateBuffer(flatBufferBuilder));
+
+    auto quantizationParameters =
+        CreateQuantizationParameters(flatBufferBuilder,
+                                     0,
+                                     0,
+                                     flatBufferBuilder.CreateVector<float>({ quantScale }),
+                                     flatBufferBuilder.CreateVector<int64_t>({ quantOffset }));
+
+    std::array<flatbuffers::Offset<Tensor>, 3> tensors;
+    tensors[0] = CreateTensor(flatBufferBuilder,
+                              flatBufferBuilder.CreateVector<int32_t>(input0TensorShape.data(),
+                                                                      input0TensorShape.size()),
+                              tensorType,
+                              1,
+                              flatBufferBuilder.CreateString("input_0"),
+                              quantizationParameters);
+    tensors[1] = CreateTensor(flatBufferBuilder,
+                              flatBufferBuilder.CreateVector<int32_t>(input1TensorShape.data(),
+                                                                      input1TensorShape.size()),
+                              tensorType,
+                              2,
+                              flatBufferBuilder.CreateString("input_1"),
+                              quantizationParameters);
+    tensors[2] = CreateTensor(flatBufferBuilder,
+                              flatBufferBuilder.CreateVector<int32_t>(outputTensorShape.data(),
+                                                                      outputTensorShape.size()),
+                              ::tflite::TensorType_BOOL,
+                              3);
+
+    // create operator
+    tflite::BuiltinOptions operatorBuiltinOptionsType = BuiltinOptions_EqualOptions;;
+    flatbuffers::Offset<void> operatorBuiltinOptions = CreateEqualOptions(flatBufferBuilder).Union();
+    switch (comparisonOperatorCode)
+    {
+        case BuiltinOperator_EQUAL:
+        {
+            operatorBuiltinOptionsType = BuiltinOptions_EqualOptions;
+            operatorBuiltinOptions = CreateEqualOptions(flatBufferBuilder).Union();
+            break;
+        }
+        case BuiltinOperator_NOT_EQUAL:
+        {
+            operatorBuiltinOptionsType = BuiltinOptions_NotEqualOptions;
+            operatorBuiltinOptions = CreateNotEqualOptions(flatBufferBuilder).Union();
+            break;
+        }
+        case BuiltinOperator_GREATER:
+        {
+            operatorBuiltinOptionsType = BuiltinOptions_GreaterOptions;
+            operatorBuiltinOptions = CreateGreaterOptions(flatBufferBuilder).Union();
+            break;
+        }
+        case BuiltinOperator_GREATER_EQUAL:
+        {
+            operatorBuiltinOptionsType = BuiltinOptions_GreaterEqualOptions;
+            operatorBuiltinOptions = CreateGreaterEqualOptions(flatBufferBuilder).Union();
+            break;
+        }
+        case BuiltinOperator_LESS:
+        {
+            operatorBuiltinOptionsType = BuiltinOptions_LessOptions;
+            operatorBuiltinOptions = CreateLessOptions(flatBufferBuilder).Union();
+            break;
+        }
+        case BuiltinOperator_LESS_EQUAL:
+        {
+            operatorBuiltinOptionsType = BuiltinOptions_LessEqualOptions;
+            operatorBuiltinOptions = CreateLessEqualOptions(flatBufferBuilder).Union();
+            break;
+        }
+        default:
+            break;
+    }
+    const std::vector<int32_t> operatorInputs{0, 1};
+    const std::vector<int32_t> operatorOutputs{2};
+    flatbuffers::Offset <Operator> comparisonOperator =
+        CreateOperator(flatBufferBuilder,
+                       0,
+                       flatBufferBuilder.CreateVector<int32_t>(operatorInputs.data(), operatorInputs.size()),
+                       flatBufferBuilder.CreateVector<int32_t>(operatorOutputs.data(), operatorOutputs.size()),
+                       operatorBuiltinOptionsType,
+                       operatorBuiltinOptions);
+
+    const std::vector<int> subgraphInputs{0, 1};
+    const std::vector<int> subgraphOutputs{2};
+    flatbuffers::Offset <SubGraph> subgraph =
+        CreateSubGraph(flatBufferBuilder,
+                       flatBufferBuilder.CreateVector(tensors.data(), tensors.size()),
+                       flatBufferBuilder.CreateVector<int32_t>(subgraphInputs.data(), subgraphInputs.size()),
+                       flatBufferBuilder.CreateVector<int32_t>(subgraphOutputs.data(), subgraphOutputs.size()),
+                       flatBufferBuilder.CreateVector(&comparisonOperator, 1));
+
+    flatbuffers::Offset <flatbuffers::String> modelDescription =
+        flatBufferBuilder.CreateString("ArmnnDelegate: Comparison Operator Model");
+    flatbuffers::Offset <OperatorCode> operatorCode = CreateOperatorCode(flatBufferBuilder, comparisonOperatorCode);
+
+    flatbuffers::Offset <Model> flatbufferModel =
+        CreateModel(flatBufferBuilder,
+                    TFLITE_SCHEMA_VERSION,
+                    flatBufferBuilder.CreateVector(&operatorCode, 1),
+                    flatBufferBuilder.CreateVector(&subgraph, 1),
+                    modelDescription,
+                    flatBufferBuilder.CreateVector(buffers.data(), buffers.size()));
+
+    flatBufferBuilder.Finish(flatbufferModel);
+
+    return std::vector<char>(flatBufferBuilder.GetBufferPointer(),
+                             flatBufferBuilder.GetBufferPointer() + flatBufferBuilder.GetSize());
+}
+
+template <typename T>
+void ComparisonTest(tflite::BuiltinOperator comparisonOperatorCode,
+                    tflite::TensorType tensorType,
+                    std::vector<armnn::BackendId>& backends,
+                    std::vector<int32_t>& input0Shape,
+                    std::vector<int32_t>& input1Shape,
+                    std::vector<int32_t>& outputShape,
+                    std::vector<T>& input0Values,
+                    std::vector<T>& input1Values,
+                    std::vector<bool>& expectedOutputValues,
+                    float quantScale = 1.0f,
+                    int quantOffset  = 0)
+{
+    using namespace tflite;
+    std::vector<char> modelBuffer = CreateComparisonTfLiteModel(comparisonOperatorCode,
+                                                                tensorType,
+                                                                input0Shape,
+                                                                input1Shape,
+                                                                outputShape,
+                                                                quantScale,
+                                                                quantOffset);
+
+    const Model* tfLiteModel = GetModel(modelBuffer.data());
+    // Create TfLite Interpreters
+    std::unique_ptr<Interpreter> armnnDelegateInterpreter;
+    CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver())
+              (&armnnDelegateInterpreter) == kTfLiteOk);
+    CHECK(armnnDelegateInterpreter != nullptr);
+    CHECK(armnnDelegateInterpreter->AllocateTensors() == kTfLiteOk);
+
+    std::unique_ptr<Interpreter> tfLiteInterpreter;
+    CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver())
+              (&tfLiteInterpreter) == kTfLiteOk);
+    CHECK(tfLiteInterpreter != nullptr);
+    CHECK(tfLiteInterpreter->AllocateTensors() == kTfLiteOk);
+
+    // Create the ArmNN Delegate
+    armnnDelegate::DelegateOptions delegateOptions(backends);
+    std::unique_ptr<TfLiteDelegate, decltype(&armnnDelegate::TfLiteArmnnDelegateDelete)>
+        theArmnnDelegate(armnnDelegate::TfLiteArmnnDelegateCreate(delegateOptions),
+                         armnnDelegate::TfLiteArmnnDelegateDelete);
+    CHECK(theArmnnDelegate != nullptr);
+    // Modify armnnDelegateInterpreter to use armnnDelegate
+    CHECK(armnnDelegateInterpreter->ModifyGraphWithDelegate(theArmnnDelegate.get()) == kTfLiteOk);
+
+    // Set input data
+    auto tfLiteDelegateInput0Id = tfLiteInterpreter->inputs()[0];
+    auto tfLiteDelageInput0Data = tfLiteInterpreter->typed_tensor<T>(tfLiteDelegateInput0Id);
+    for (unsigned int i = 0; i < input0Values.size(); ++i)
+    {
+        tfLiteDelageInput0Data[i] = input0Values[i];
+    }
+
+    auto tfLiteDelegateInput1Id = tfLiteInterpreter->inputs()[1];
+    auto tfLiteDelageInput1Data = tfLiteInterpreter->typed_tensor<T>(tfLiteDelegateInput1Id);
+    for (unsigned int i = 0; i < input1Values.size(); ++i)
+    {
+        tfLiteDelageInput1Data[i] = input1Values[i];
+    }
+
+    auto armnnDelegateInput0Id = armnnDelegateInterpreter->inputs()[0];
+    auto armnnDelegateInput0Data = armnnDelegateInterpreter->typed_tensor<T>(armnnDelegateInput0Id);
+    for (unsigned int i = 0; i < input0Values.size(); ++i)
+    {
+        armnnDelegateInput0Data[i] = input0Values[i];
+    }
+
+    auto armnnDelegateInput1Id = armnnDelegateInterpreter->inputs()[1];
+    auto armnnDelegateInput1Data = armnnDelegateInterpreter->typed_tensor<T>(armnnDelegateInput1Id);
+    for (unsigned int i = 0; i < input1Values.size(); ++i)
+    {
+        armnnDelegateInput1Data[i] = input1Values[i];
+    }
+
+    // Run EnqueWorkload
+    CHECK(tfLiteInterpreter->Invoke() == kTfLiteOk);
+    CHECK(armnnDelegateInterpreter->Invoke() == kTfLiteOk);
+    // Compare output data
+    auto tfLiteDelegateOutputId = tfLiteInterpreter->outputs()[0];
+    auto tfLiteDelageOutputData = tfLiteInterpreter->typed_tensor<bool>(tfLiteDelegateOutputId);
+    auto armnnDelegateOutputId = armnnDelegateInterpreter->outputs()[0];
+    auto armnnDelegateOutputData = armnnDelegateInterpreter->typed_tensor<bool>(armnnDelegateOutputId);
+
+    armnnDelegate::CompareData(expectedOutputValues  , armnnDelegateOutputData, expectedOutputValues.size());
+    armnnDelegate::CompareData(expectedOutputValues  , tfLiteDelageOutputData , expectedOutputValues.size());
+    armnnDelegate::CompareData(tfLiteDelageOutputData, armnnDelegateOutputData, expectedOutputValues.size());
+}
+
+} // anonymous namespace
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