diff --git a/delegate/src/test/GatherNdTestHelper.hpp b/delegate/src/test/GatherNdTestHelper.hpp
new file mode 100644
index 0000000..f475584
--- /dev/null
+++ b/delegate/src/test/GatherNdTestHelper.hpp
@@ -0,0 +1,178 @@
+//
+// Copyright © 2022 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 <tensorflow/lite/schema/schema_generated.h>
+#include <tensorflow/lite/version.h>
+
+#include <doctest/doctest.h>
+
+namespace
+{
+
+std::vector<char> CreateGatherNdTfLiteModel(tflite::TensorType tensorType,
+                                          std::vector<int32_t>& paramsShape,
+                                          std::vector<int32_t>& indicesShape,
+                                          const std::vector<int32_t>& expectedOutputShape,
+                                          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, flatBufferBuilder.CreateVector({})));
+
+    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>(paramsShape.data(),
+                                                                      paramsShape.size()),
+                              tensorType,
+                              0,
+                              flatBufferBuilder.CreateString("params"),
+                              quantizationParameters);
+    tensors[1] = CreateTensor(flatBufferBuilder,
+                              flatBufferBuilder.CreateVector<int32_t>(indicesShape.data(),
+                                                                      indicesShape.size()),
+                              ::tflite::TensorType_INT32,
+                              0,
+                              flatBufferBuilder.CreateString("indices"),
+                              quantizationParameters);
+    tensors[2] = CreateTensor(flatBufferBuilder,
+                              flatBufferBuilder.CreateVector<int32_t>(expectedOutputShape.data(),
+                                                                      expectedOutputShape.size()),
+                              tensorType,
+                              0,
+                              flatBufferBuilder.CreateString("output"),
+                              quantizationParameters);
+
+
+    // create operator
+    tflite::BuiltinOptions    operatorBuiltinOptionsType = tflite::BuiltinOptions_GatherNdOptions;
+    flatbuffers::Offset<void> operatorBuiltinOptions     = CreateGatherNdOptions(flatBufferBuilder).Union();
+
+    const std::vector<int>        operatorInputs{{0, 1}};
+    const std::vector<int>        operatorOutputs{2};
+    flatbuffers::Offset<Operator> controlOperator        =
+                                      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(&controlOperator, 1));
+
+    flatbuffers::Offset<flatbuffers::String> modelDescription =
+                                             flatBufferBuilder.CreateString("ArmnnDelegate: GATHER_ND Operator Model");
+    flatbuffers::Offset<OperatorCode>        operatorCode     = CreateOperatorCode(flatBufferBuilder,
+                                                                                   BuiltinOperator_GATHER_ND);
+
+    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 GatherNdTest(tflite::TensorType tensorType,
+                std::vector<armnn::BackendId>& backends,
+                std::vector<int32_t>& paramsShape,
+                std::vector<int32_t>& indicesShape,
+                std::vector<int32_t>& expectedOutputShape,
+                std::vector<T>& paramsValues,
+                std::vector<int32_t>& indicesValues,
+                std::vector<T>& expectedOutputValues,
+                float quantScale = 1.0f,
+                int quantOffset = 0)
+{
+    using namespace tflite;
+    std::vector<char> modelBuffer = CreateGatherNdTfLiteModel(tensorType,
+                                                            paramsShape,
+                                                            indicesShape,
+                                                            expectedOutputShape,
+                                                            quantScale,
+                                                            quantOffset);
+    const Model* tfLiteModel = GetModel(modelBuffer.data());
+
+    // Create TfLite Interpreters
+    std::unique_ptr<Interpreter> armnnDelegate;
+    CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver())
+              (&armnnDelegate) == kTfLiteOk);
+    CHECK(armnnDelegate != nullptr);
+    CHECK(armnnDelegate->AllocateTensors() == kTfLiteOk);
+
+    std::unique_ptr<Interpreter> tfLiteDelegate;
+    CHECK(InterpreterBuilder(tfLiteModel, ::tflite::ops::builtin::BuiltinOpResolver())
+              (&tfLiteDelegate) == kTfLiteOk);
+    CHECK(tfLiteDelegate != nullptr);
+    CHECK(tfLiteDelegate->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(armnnDelegate->ModifyGraphWithDelegate(theArmnnDelegate.get()) == kTfLiteOk);
+
+    // Set input data
+    armnnDelegate::FillInput<T>(tfLiteDelegate, 0, paramsValues);
+    armnnDelegate::FillInput<T>(armnnDelegate, 0, paramsValues);
+    armnnDelegate::FillInput<int32_t>(tfLiteDelegate, 1, indicesValues);
+    armnnDelegate::FillInput<int32_t>(armnnDelegate, 1, indicesValues);
+
+    // Run EnqueWorkload
+    CHECK(tfLiteDelegate->Invoke() == kTfLiteOk);
+    CHECK(armnnDelegate->Invoke() == kTfLiteOk);
+
+    // Compare output data
+    armnnDelegate::CompareOutputData<T>(tfLiteDelegate,
+                                        armnnDelegate,
+                                        expectedOutputShape,
+                                        expectedOutputValues,
+                                        0);
+
+    tfLiteDelegate.reset(nullptr);
+    armnnDelegate.reset(nullptr);
+}
+} // anonymous namespace
\ No newline at end of file