diff --git a/test/1.2/Mean.cpp b/test/1.2/Mean.cpp
new file mode 100644
index 0000000..a2a8b7a
--- /dev/null
+++ b/test/1.2/Mean.cpp
@@ -0,0 +1,204 @@
+//
+// Copyright © 2022 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "../DriverTestHelpers.hpp"
+#include "../TestHalfTensor.hpp"
+
+#include <1.2/HalPolicy.hpp>
+
+#include <array>
+
+using Half = half_float::half;
+
+using namespace android::hardware;
+using namespace driverTestHelpers;
+using namespace armnn_driver;
+
+using HalPolicy = hal_1_2::HalPolicy;
+using RequestArgument = V1_0::RequestArgument;
+
+namespace
+{
+
+void MeanTestImpl(const TestHalfTensor& input,
+                  const hidl_vec<uint32_t>& axisDimensions,
+                  const int32_t* axisValues,
+                  int32_t keepDims,
+                  const TestHalfTensor& expectedOutput,
+                  bool fp16Enabled,
+                  armnn::Compute computeDevice)
+{
+    auto driver = std::make_unique<ArmnnDriver>(DriverOptions(computeDevice, fp16Enabled));
+
+    HalPolicy::Model model = {};
+
+    AddInputOperand<HalPolicy>(model, input.GetDimensions(), V1_2::OperandType::TENSOR_FLOAT16);
+
+    AddTensorOperand<HalPolicy>(model,
+                                axisDimensions,
+                                const_cast<int32_t*>(axisValues),
+                                HalPolicy::OperandType::TENSOR_INT32);
+
+    AddIntOperand<HalPolicy>(model, keepDims);
+
+    AddOutputOperand<HalPolicy>(model, expectedOutput.GetDimensions(), V1_2::OperandType::TENSOR_FLOAT16);
+
+    model.operations.resize(1);
+    model.operations[0].type               = HalPolicy::OperationType::MEAN;
+    model.operations[0].inputs             = hidl_vec<uint32_t>{ 0, 1, 2 };
+    model.operations[0].outputs            = hidl_vec<uint32_t>{ 3 };
+    model.relaxComputationFloat32toFloat16 = fp16Enabled;
+
+    //android::sp<V1_0::IPreparedModel> preparedModel = PrepareModel(model, *driver);
+    android::sp<V1_2::IPreparedModel> preparedModel = PrepareModel_1_2(model, *driver);
+
+    // The request's memory pools will follow the same order as the inputs
+    V1_0::DataLocation inLoc = {};
+    inLoc.poolIndex          = 0;
+    inLoc.offset             = 0;
+    inLoc.length             = input.GetNumElements() * sizeof(Half);
+    RequestArgument inArg    = {};
+    inArg.location           = inLoc;
+    inArg.dimensions         = input.GetDimensions();
+
+    // An additional memory pool is needed for the output
+    V1_0::DataLocation outLoc = {};
+    outLoc.poolIndex          = 1;
+    outLoc.offset             = 0;
+    outLoc.length             = expectedOutput.GetNumElements() * sizeof(Half);
+    RequestArgument outArg    = {};
+    outArg.location           = outLoc;
+    outArg.dimensions         = expectedOutput.GetDimensions();
+
+    // Make the request based on the arguments
+    V1_0::Request request = {};
+    request.inputs  = hidl_vec<RequestArgument>{ inArg };
+    request.outputs = hidl_vec<RequestArgument>{ outArg };
+
+    // Set the input data
+    AddPoolAndSetData(input.GetNumElements(), request, input.GetData());
+
+    // Add memory for the output
+    android::sp<IMemory> outMemory = AddPoolAndGetData<Half>(expectedOutput.GetNumElements(), request);
+    const Half* outputData = static_cast<const Half*>(static_cast<void*>(outMemory->getPointer()));
+
+    if (preparedModel.get() != nullptr)
+    {
+        V1_0::ErrorStatus execStatus = Execute(preparedModel, request);
+        DOCTEST_CHECK((int)execStatus == (int)V1_0::ErrorStatus::NONE);
+    }
+
+    const Half* expectedOutputData = expectedOutput.GetData();
+    for (unsigned int i = 0; i < expectedOutput.GetNumElements(); i++)
+    {
+        DOCTEST_CHECK(outputData[i] == expectedOutputData[i]);
+    }
+}
+
+} // anonymous namespace
+
+DOCTEST_TEST_SUITE("MeanTests_1.2_CpuRef")
+{
+
+DOCTEST_TEST_CASE("MeanFp16NoKeepDimsTest_CpuRef")
+{
+    using namespace half_float::literal;
+
+    TestHalfTensor input{ armnn::TensorShape{ 4, 3, 2 },
+                      { 1.0_h, 2.0_h, 3.0_h, 4.0_h, 5.0_h, 6.0_h, 7.0_h, 8.0_h, 9.0_h, 10.0_h,
+                        11.0_h, 12.0_h, 13.0_h, 14.0_h, 15.0_h, 16.0_h, 17.0_h, 18.0_h, 19.0_h,
+                        20.0_h, 21.0_h, 22.0_h, 23.0_h, 24.0_h } };
+    hidl_vec<uint32_t> axisDimensions = { 2 };
+    int32_t axisValues[] = { 0, 1 };
+    int32_t keepDims = 0;
+    TestHalfTensor expectedOutput{ armnn::TensorShape{ 2 }, { 12.0_h, 13.0_h } };
+
+    MeanTestImpl(input, axisDimensions, axisValues, keepDims, expectedOutput, true, armnn::Compute::CpuRef);
+}
+
+DOCTEST_TEST_CASE("MeanFp16KeepDimsTest_CpuRef")
+{
+    using namespace half_float::literal;
+
+    TestHalfTensor input{ armnn::TensorShape{ 1, 1, 3, 2 }, { 1.0_h, 1.0_h, 2.0_h, 2.0_h, 3.0_h, 3.0_h } };
+    hidl_vec<uint32_t> axisDimensions = { 1 };
+    int32_t axisValues[] = { 2 };
+    int32_t keepDims = 1;
+    TestHalfTensor expectedOutput{ armnn::TensorShape{ 1, 1, 1, 2 }, {  2.0_h, 2.0_h } };
+
+    MeanTestImpl(input, axisDimensions, axisValues, keepDims, expectedOutput, true, armnn::Compute::CpuRef);
+}
+
+}
+
+#ifdef ARMCOMPUTECL_ENABLED
+DOCTEST_TEST_SUITE("MeanTests_1.2_CpuAcc")
+{
+    DOCTEST_TEST_CASE("MeanFp16NoKeepDimsTest_CpuAcc")
+    {
+        using namespace half_float::literal;
+
+        std::vector<Half> in = { 1.0_h, 2.0_h, 3.0_h, 4.0_h, 5.0_h, 6.0_h, 7.0_h, 8.0_h, 9.0_h, 10.0_h,
+                            11.0_h, 12.0_h, 13.0_h, 14.0_h, 15.0_h, 16.0_h, 17.0_h, 18.0_h, 19.0_h,
+                            20.0_h, 21.0_h, 22.0_h, 23.0_h, 24.0_h };
+        TestHalfTensor input{ armnn::TensorShape{ 4, 3, 2 },
+                           in};
+        hidl_vec<uint32_t> axisDimensions = { 2 };
+        int32_t axisValues[] = { 0, 1 };
+        int32_t keepDims = 0;
+        std::vector<Half> out = { 12.0_h, 13.0_h };
+        TestHalfTensor expectedOutput{ armnn::TensorShape{ 2 }, out };
+
+        MeanTestImpl(input, axisDimensions, axisValues, keepDims, expectedOutput, true, armnn::Compute::CpuAcc);
+    }
+
+    DOCTEST_TEST_CASE("MeanFp16KeepDimsTest_CpuAcc")
+    {
+        using namespace half_float::literal;
+
+        std::vector<Half> in = { 1.0_h, 1.0_h, 2.0_h, 2.0_h, 3.0_h, 3.0_h };
+        TestHalfTensor input{ armnn::TensorShape{ 1, 1, 3, 2 }, in };
+        hidl_vec<uint32_t> axisDimensions = { 1 };
+        int32_t axisValues[] = { 2 };
+        int32_t keepDims = 1;
+        std::vector<Half> out = {  2.0_h, 2.0_h };
+        TestHalfTensor expectedOutput{ armnn::TensorShape{ 1, 1, 1, 2 }, out };
+
+        MeanTestImpl(input, axisDimensions, axisValues, keepDims, expectedOutput, true, armnn::Compute::CpuAcc);
+    }
+}
+
+DOCTEST_TEST_SUITE("MeanTests_1.2_GpuAcc")
+{
+    DOCTEST_TEST_CASE("MeanFp16NoKeepDimsTest_GpuAcc")
+    {
+        using namespace half_float::literal;
+
+        TestHalfTensor input{ armnn::TensorShape{ 4, 3, 2 },
+                          { 1.0_h, 2.0_h, 3.0_h, 4.0_h, 5.0_h, 6.0_h, 7.0_h, 8.0_h, 9.0_h, 10.0_h,
+                            11.0_h, 12.0_h, 13.0_h, 14.0_h, 15.0_h, 16.0_h, 17.0_h, 18.0_h, 19.0_h,
+                            20.0_h, 21.0_h, 22.0_h, 23.0_h, 24.0_h } };
+        hidl_vec<uint32_t> axisDimensions = { 2 };
+        int32_t axisValues[] = { 0, 1 };
+        int32_t keepDims = 0;
+        TestHalfTensor expectedOutput{ armnn::TensorShape{ 2 }, { 12.0_h, 13.0_h } };
+
+        MeanTestImpl(input, axisDimensions, axisValues, keepDims, expectedOutput, true, armnn::Compute::GpuAcc);
+    }
+
+    DOCTEST_TEST_CASE("MeanFp16KeepDimsTest_GpuAcc")
+    {
+        using namespace half_float::literal;
+
+        TestHalfTensor input{ armnn::TensorShape{ 1, 1, 3, 2 }, { 1.0_h, 1.0_h, 2.0_h, 2.0_h, 3.0_h, 3.0_h } };
+        hidl_vec<uint32_t> axisDimensions = { 1 };
+        int32_t axisValues[] = { 2 };
+        int32_t keepDims = 1;
+        TestHalfTensor expectedOutput{ armnn::TensorShape{ 1, 1, 1, 2 }, {  2.0_h, 2.0_h } };
+
+        MeanTestImpl(input, axisDimensions, axisValues, keepDims, expectedOutput, true, armnn::Compute::GpuAcc);
+    }
+}
+#endif