diff --git a/ArmnnPreparedModel_1_2.hpp b/ArmnnPreparedModel_1_2.hpp
new file mode 100644
index 0000000..4e883b6
--- /dev/null
+++ b/ArmnnPreparedModel_1_2.hpp
@@ -0,0 +1,80 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#pragma once
+
+#include "ArmnnDriver.hpp"
+#include "ArmnnDriverImpl.hpp"
+#include "RequestThread.hpp"
+#include "ModelToINetworkConverter.hpp"
+
+#include <NeuralNetworks.h>
+#include <armnn/ArmNN.hpp>
+
+#include <string>
+#include <vector>
+
+namespace armnn_driver
+{
+
+template <typename HalVersion>
+class ArmnnPreparedModel_1_2 : public V1_2::IPreparedModel
+{
+public:
+    using HalModel = typename V1_2::Model;
+
+    ArmnnPreparedModel_1_2(armnn::NetworkId networkId,
+                           armnn::IRuntime* runtime,
+                           const HalModel& model,
+                           const std::string& requestInputsAndOutputsDumpDir,
+                           const bool gpuProfilingEnabled);
+
+    virtual ~ArmnnPreparedModel_1_2();
+
+    virtual Return<ErrorStatus> execute(const Request& request,
+                                        const ::android::sp<V1_0::IExecutionCallback>& callback) override;
+
+    virtual Return<ErrorStatus> execute_1_2(const Request& request, MeasureTiming measure,
+                                            const sp<V1_2::IExecutionCallback>& callback) override;
+
+    virtual Return<void> executeSynchronously(const Request &request,
+                                              MeasureTiming measure,
+                                              V1_2::IPreparedModel::executeSynchronously_cb cb) override;
+
+    virtual Return<void> configureExecutionBurst(
+            const sp<V1_2::IBurstCallback>& callback,
+            const android::hardware::MQDescriptorSync<V1_2::FmqRequestDatum>& requestChannel,
+            const android::hardware::MQDescriptorSync<V1_2::FmqResultDatum>& resultChannel,
+            configureExecutionBurst_cb cb) override;
+
+    /// execute the graph prepared from the request
+    void ExecuteGraph(std::shared_ptr<std::vector<::android::nn::RunTimePoolInfo>>& pMemPools,
+                      std::shared_ptr<armnn::InputTensors>& pInputTensors,
+                      std::shared_ptr<armnn::OutputTensors>& pOutputTensors,
+                      const ::android::sp<V1_0::IExecutionCallback>& callback);
+
+    /// Executes this model with dummy inputs (e.g. all zeroes).
+    /// \return false on failure, otherwise true
+    bool ExecuteWithDummyInputs();
+
+private:
+    template <typename ExecutionCallback>
+    Return <ErrorStatus> Execute(const Request &request, const sp <ExecutionCallback> &callback);
+
+    template <typename TensorBindingCollection>
+    void DumpTensorsIfRequired(char const* tensorNamePrefix, const TensorBindingCollection& tensorBindings);
+
+    armnn::NetworkId                                         m_NetworkId;
+    armnn::IRuntime*                                         m_Runtime;
+    V1_2::Model                                              m_Model;
+    // There must be a single RequestThread for all ArmnnPreparedModel objects to ensure serial execution of workloads
+    // It is specific to this class, so it is declared as static here
+    static RequestThread<ArmnnPreparedModel_1_2, HalVersion> m_RequestThread;
+    uint32_t                                                 m_RequestCount;
+    const std::string&                                       m_RequestInputsAndOutputsDumpDir;
+    const bool                                               m_GpuProfilingEnabled;
+};
+
+}