diff --git a/neuralnetworks/1.0/Android.bp b/neuralnetworks/1.0/Android.bp
index d7c3bbb..ba32d0c 100644
--- a/neuralnetworks/1.0/Android.bp
+++ b/neuralnetworks/1.0/Android.bp
@@ -5,8 +5,9 @@
     srcs: [
         "types.hal",
         "IDevice.hal",
-        "IEvent.hal",
+        "IExecutionCallback.hal",
         "IPreparedModel.hal",
+        "IPreparedModelCallback.hal",
     ],
 }
 
@@ -20,8 +21,9 @@
     out: [
         "android/hardware/neuralnetworks/1.0/types.cpp",
         "android/hardware/neuralnetworks/1.0/DeviceAll.cpp",
-        "android/hardware/neuralnetworks/1.0/EventAll.cpp",
+        "android/hardware/neuralnetworks/1.0/ExecutionCallbackAll.cpp",
         "android/hardware/neuralnetworks/1.0/PreparedModelAll.cpp",
+        "android/hardware/neuralnetworks/1.0/PreparedModelCallbackAll.cpp",
     ],
 }
 
@@ -40,16 +42,21 @@
         "android/hardware/neuralnetworks/1.0/BnHwDevice.h",
         "android/hardware/neuralnetworks/1.0/BpHwDevice.h",
         "android/hardware/neuralnetworks/1.0/BsDevice.h",
-        "android/hardware/neuralnetworks/1.0/IEvent.h",
-        "android/hardware/neuralnetworks/1.0/IHwEvent.h",
-        "android/hardware/neuralnetworks/1.0/BnHwEvent.h",
-        "android/hardware/neuralnetworks/1.0/BpHwEvent.h",
-        "android/hardware/neuralnetworks/1.0/BsEvent.h",
+        "android/hardware/neuralnetworks/1.0/IExecutionCallback.h",
+        "android/hardware/neuralnetworks/1.0/IHwExecutionCallback.h",
+        "android/hardware/neuralnetworks/1.0/BnHwExecutionCallback.h",
+        "android/hardware/neuralnetworks/1.0/BpHwExecutionCallback.h",
+        "android/hardware/neuralnetworks/1.0/BsExecutionCallback.h",
         "android/hardware/neuralnetworks/1.0/IPreparedModel.h",
         "android/hardware/neuralnetworks/1.0/IHwPreparedModel.h",
         "android/hardware/neuralnetworks/1.0/BnHwPreparedModel.h",
         "android/hardware/neuralnetworks/1.0/BpHwPreparedModel.h",
         "android/hardware/neuralnetworks/1.0/BsPreparedModel.h",
+        "android/hardware/neuralnetworks/1.0/IPreparedModelCallback.h",
+        "android/hardware/neuralnetworks/1.0/IHwPreparedModelCallback.h",
+        "android/hardware/neuralnetworks/1.0/BnHwPreparedModelCallback.h",
+        "android/hardware/neuralnetworks/1.0/BpHwPreparedModelCallback.h",
+        "android/hardware/neuralnetworks/1.0/BsPreparedModelCallback.h",
     ],
 }
 
diff --git a/neuralnetworks/1.0/IDevice.hal b/neuralnetworks/1.0/IDevice.hal
index 91a9555..49c2967 100644
--- a/neuralnetworks/1.0/IDevice.hal
+++ b/neuralnetworks/1.0/IDevice.hal
@@ -16,8 +16,7 @@
 
 package android.hardware.neuralnetworks@1.0;
 
-import IEvent;
-import IPreparedModel;
+import IPreparedModelCallback;
 
 /**
  * This interface represents a device driver.
@@ -37,10 +36,9 @@
     /**
      * Gets the supported operations in a model.
      *
-     * getSupportedSubgraph provides a more nuanced indication on whether a
-     * model is able to be compiled by the driver. Having the entire model
-     * allows for additional information such as tensor shapes to inputs or
-     * tensor strides, information which is not known in "initialize".
+     * getSupportedSubgraph indicates which operations of a model are fully
+     * supported by the vendor driver. If an operation may not be supported for
+     * any reason, getSupportedOperations must return false for that operation.
      *
      * @param model A model whose operations--and their corresponding
      *              operands--are to be verified by the driver.
@@ -48,7 +46,7 @@
      *                - NONE if successful
      *                - DEVICE_UNAVAILABLE if driver is offline or busy
      *                - GENERAL_FAILURE if there is an unspecified error
-     *                - INVALID_ARGUMENT when provided model is invalid
+     *                - INVALID_ARGUMENT if provided model is invalid
      * @return supportedOperations A list of supported operations, where true
      *                             indicates the operation is supported and
      *                             false indicates the operation is not
@@ -60,29 +58,60 @@
                 generates (ErrorStatus status, vec<bool> supportedOperations);
 
     /**
-     * Prepares a model for execution.
+     * Creates a prepared model for execution.
      *
      * prepareModel is used to make any necessary transformations or alternative
-     * representations to a model for execution, possible including
+     * representations to a model for execution, possiblly including
      * transformations on the constant data, optimization on the model's graph,
-     * or compilation into the device's native binary format.
+     * or compilation into the device's native binary format. The model itself
+     * is not changed.
+     *
+     * The model is prepared asynchronously with respect to the caller. The
+     * prepareModel function must verify the inputs to the prepareModel function
+     * are correct. If there is an error, prepareModel must immediately invoke
+     * the callback with the appropriate ErrorStatus value and nullptr for the
+     * IPreparedModel, then return with the same ErrorStatus. If the inputs to
+     * the prepareModel function are valid and there is no error, prepareModel
+     * must launch an asynchronous task to prepare the model in the background,
+     * and immediately return from prepareModel with ErrorStatus::NONE. If the
+     * asynchronous task fails to launch, prepareModel must immediately invoke
+     * the callback with ErrorStatus::GENERAL_FAILURE and nullptr for the
+     * IPreparedModel, then return with ErrorStatus::GENERAL_FAILURE.
+     *
+     * When the asynchronous task has finished preparing the model, it must
+     * immediately invoke the callback function provided as an input to
+     * prepareModel. If the model was prepared successfully, the callback object
+     * must be invoked with an error status of ErrorStatus::NONE and the
+     * produced IPreparedModel object. If an error occurred preparing the model,
+     * the callback object must be invoked with the appropriate ErrorStatus
+     * value and nullptr for the IPreparedModel.
      *
      * The only information that may be unknown to the model at this stage is
-     * the shape of the tensors, which may only be known at execution time.
+     * the shape of the tensors, which may only be known at execution time. As
+     * such, some driver services may return partially prepared models, where
+     * the prepared model can only be finished when it is paired with a set of
+     * inputs to the model. Note that the same prepared model object can be
+     * used with different shapes of inputs on different (possibly concurrent)
+     * executions.
+     *
+     * Multiple threads can call prepareModel on the same model concurrently.
      *
      * @param model The model to be prepared for execution.
-     * @param event A synchronization callback that must be signaled once the
-     *              execution has finished.
-     * @return status Error status of the call, must be:
+     * @param callback A callback object used to return the error status of
+     *                 preparing the model for execution and the prepared model
+     *                 if successful, nullptr otherwise. The callback object's
+     *                 notify function must be called exactly once, even if the
+     *                 model could not be prepared.
+     * @return status Error status of launching a task which prepares the model
+     *                in the background; must be:
      *                - NONE if preparation task is successfully launched
      *                - DEVICE_UNAVAILABLE if driver is offline or busy
      *                - GENERAL_FAILURE if there is an unspecified error
-     *                - INVALID_ARGUMENT when one of the input arguments is
+     *                - INVALID_ARGUMENT if one of the input arguments is
      *                  invalid
-     * @return preparedModel A handle to the resultant prepared model.
      */
-    prepareModel(Model model, IEvent event)
-      generates (ErrorStatus status, IPreparedModel preparedModel);
+    prepareModel(Model model, IPreparedModelCallback callback)
+      generates (ErrorStatus status);
 
     /**
      * Returns the current status of a driver.
diff --git a/neuralnetworks/1.0/IEvent.hal b/neuralnetworks/1.0/IEvent.hal
deleted file mode 100644
index 2fe454c..0000000
--- a/neuralnetworks/1.0/IEvent.hal
+++ /dev/null
@@ -1,45 +0,0 @@
-/*
- * Copyright (C) 2017 The Android Open Source Project
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-
-package android.hardware.neuralnetworks@1.0;
-
-/**
- * The IEvent interface is a callback object passed by the
- * Neuralnetworks runtime to the vendor service. It is used as a
- * synchronization primitive between one or more runtime threads and a
- * single asynchronous vendor thread.  An event object is passed as an
- * argument to a HIDL call that is expected to take a non-trivial
- * amount of time. When the asynchronous execution thread has
- * completed its computation, it must call "notify" on the event to
- * indicate to the Neuralnetworks runtime whether the computation was
- * successful or not, and that the corresponding output is ready to be
- * consumed if the execution was successful.
- */
-interface IEvent {
-
-    /**
-     * IEvent::notify is called by the server thread (i.e., the thread doing
-     * the work) to mark the event as completed so that any threads requiring
-     * the corresponding output can continue executing.
-     *
-     * @param status Error status returned from the asynchronous task, must be:
-     *               - NONE if asynchronous task was successful
-     *               - DEVICE_UNAVAILABLE if driver is offline or busy
-     *               - GENERAL_FAILURE if the asynchronous task resulted in an
-     *                 unspecified error
-     */
-    oneway notify(ErrorStatus status);
-};
diff --git a/neuralnetworks/1.0/IExecutionCallback.hal b/neuralnetworks/1.0/IExecutionCallback.hal
new file mode 100644
index 0000000..ef0f454
--- /dev/null
+++ b/neuralnetworks/1.0/IExecutionCallback.hal
@@ -0,0 +1,44 @@
+/*
+ * Copyright (C) 2017 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks@1.0;
+
+/**
+ * IExecutionCallback must be used to return the error status result from an
+ * execution asynchronously launched from IPreparedModel::execute.
+ */
+interface IExecutionCallback {
+
+    /**
+     * notify must be invoked immediately after the asynchronous task has
+     * finished performing the execution. notify must be provided with the
+     * ErrorStatus resulting from the execution. If the asynchronous task
+     * is not launched, notify must be invoked with the appropriate error.
+     *
+     * @return param Error status returned from launching the asynchronous task
+     *               (if the launch fails) or from the asynchronous task itself
+     *               (if the launch succeeds). Must be:
+     *               - NONE if the asynchronous execution was successful
+     *               - DEVICE_UNAVAILABLE if driver is offline or busy
+     *               - GENERAL_FAILURE if the asynchronous task resulted in an
+     *                 unspecified error
+     *               - OUTPUT_INSUFFICIENT_SIZE if provided output buffer is
+     *                 not large enough to store the resultant values
+     *               - INVALID_ARGUMENT if one of the input arguments to
+     *                 prepareModel is invalid
+     */
+    oneway notify(ErrorStatus status);
+};
diff --git a/neuralnetworks/1.0/IPreparedModel.hal b/neuralnetworks/1.0/IPreparedModel.hal
index 5df883e..ee406fb 100644
--- a/neuralnetworks/1.0/IPreparedModel.hal
+++ b/neuralnetworks/1.0/IPreparedModel.hal
@@ -16,7 +16,7 @@
 
 package android.hardware.neuralnetworks@1.0;
 
-import IEvent;
+import IExecutionCallback;
 
 /**
  * IPreparedModel describes a model that has been prepared for execution and
@@ -24,28 +24,42 @@
  */
 interface IPreparedModel {
     /**
-     * Spawns an asynchronous execution on a prepared model.
+     * Launches an asynchronous execution on a prepared model.
      *
-     * Executions are asynchronous with respect to the Neuralnetworks runtime.
-     * To support this, IPreparedModel::execute must spawn a new task and return
-     * whether the task was successfully launched. The asynchronous task which
-     * performs the execution must call event's IEvent::notify with the status
-     * of the execution immediately after the execution has finished.
+     * The execution is performed asynchronously with respect to the caller.
+     * execute must verify the inputs to the function are correct. If there is
+     * an error, execute must immediately invoke the callback with the
+     * appropriate ErrorStatus value, then return with the same ErrorStatus. If
+     * the inputs to the function are valid and there is no error, execute must
+     * launch an asynchronous task to perform the execution in the background,
+     * and immediately return with ErrorStatus::NONE. If the asynchronous task
+     * fails to launch, execute must immediately invoke the callback with
+     * ErrorStatus::GENERAL_FAILURE, then return with
+     * ErrorStatus::GENERAL_FAILURE.
      *
-     * Multiple threads can call this execute function concurrently.
+     * When the asynchronous task has finished its execution, it must
+     * immediately invoke the callback object provided as an input to the
+     * execute function. This callback must be provided with the ErrorStatus of
+     * the execution.
+     *
+     * Multiple threads can call the execute function on the same IPreparedModel
+     * object concurrently with different requests.
      *
      * @param request The input and output information on which the prepared
      *                model is to be executed.
-     * @param event A callback used for synchronization that must be signaled
-     *              once the execution has finished.
+     * @param callback A callback object used to return the error status of
+     *                 the execution. The callback object's notify function must
+     *                 be called exactly once, even if the execution was
+     *                 unsuccessful.
      * @return status Error status of the call, must be:
      *                - NONE if task is successfully launched
      *                - DEVICE_UNAVAILABLE if driver is offline or busy
      *                - GENERAL_FAILURE if there is an unspecified error
      *                - OUTPUT_INSUFFICIENT_SIZE if provided output buffer is
      *                  not large enough to store the resultant values
-     *                - INVALID_ARGUMENT when one of the input arguments is
+     *                - INVALID_ARGUMENT if one of the input arguments is
      *                  invalid
      */
-    execute(Request request, IEvent event) generates (ErrorStatus status);
+    execute(Request request, IExecutionCallback callback)
+        generates (ErrorStatus status);
 };
diff --git a/neuralnetworks/1.0/IPreparedModelCallback.hal b/neuralnetworks/1.0/IPreparedModelCallback.hal
new file mode 100644
index 0000000..fa1bf9d
--- /dev/null
+++ b/neuralnetworks/1.0/IPreparedModelCallback.hal
@@ -0,0 +1,53 @@
+/*
+ * Copyright (C) 2017 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks@1.0;
+
+import IPreparedModel;
+
+/**
+ * IPreparedModelCallback must be used to return a prepared model produced by an
+ * asynchronous task launched from IDevice::prepareModel.
+ */
+interface IPreparedModelCallback {
+
+    /**
+     * notify must be invoked immediately after the asynchronous task holding
+     * this callback has finished preparing the model. If the model was
+     * successfully prepared, notify must be invoked with ErrorStatus::NONE and
+     * the prepared model. If the model was not able to be successfully
+     * prepared, notify must be invoked with the appropriate ErrorStatus and
+     * nullptr as the IPreparedModel. If the asynchronous task holding this
+     * callback fails to launch or if the model provided to
+     * IDevice::prepareModel is invalid, notify must be invoked with the
+     * appropriate error as well as nullptr for the IPreparedModel.
+     *
+     * @param status Error status returned from the asynchronous model
+     *               preparation task; must be:
+     *               - NONE if the asynchronous task successfully prepared the
+     *                 model
+     *               - DEVICE_UNAVAILABLE if driver is offline or busy
+     *               - GENERAL_FAILURE if the asynchronous task resulted in an
+     *                 unspecified error
+     *               - INVALID_ARGUMENT if one of the input arguments to
+     *                 prepareModel is invalid
+     * @param preparedModel A model that has been asynchronously prepared for
+     *                      execution. If the model was unable to be prepared
+     *                      due to an error, nullptr must be passed in place of
+     *                      the IPreparedModel object.
+     */
+    oneway notify(ErrorStatus status, IPreparedModel preparedModel);
+};
diff --git a/neuralnetworks/1.0/vts/functional/Android.bp b/neuralnetworks/1.0/vts/functional/Android.bp
index 89e1021..e33ee77 100644
--- a/neuralnetworks/1.0/vts/functional/Android.bp
+++ b/neuralnetworks/1.0/vts/functional/Android.bp
@@ -17,7 +17,7 @@
 cc_test {
     name: "VtsHalNeuralnetworksV1_0TargetTest",
     srcs: [
-        "Event.cpp",
+        "Callbacks.cpp",
         "GeneratedTestHarness.cpp",
         "Models.cpp",
         "VtsHalNeuralnetworksV1_0TargetTest.cpp",
diff --git a/neuralnetworks/1.0/vts/functional/Callbacks.cpp b/neuralnetworks/1.0/vts/functional/Callbacks.cpp
new file mode 100644
index 0000000..46bf243
--- /dev/null
+++ b/neuralnetworks/1.0/vts/functional/Callbacks.cpp
@@ -0,0 +1,127 @@
+#include "Callbacks.h"
+#include <android-base/logging.h>
+
+namespace android {
+namespace hardware {
+namespace neuralnetworks {
+namespace V1_0 {
+namespace implementation {
+
+CallbackBase::CallbackBase() : mNotified(false) {}
+
+CallbackBase::~CallbackBase() {
+    // Note that we cannot call CallbackBase::join_thread from here:
+    // CallbackBase is intended to be reference counted, and it is possible that
+    // the reference count drops to zero in the bound thread, causing the
+    // bound thread to call this destructor. If a thread tries to join
+    // itself, it throws an exception, producing a message like the
+    // following:
+    //
+    //     terminating with uncaught exception of type std::__1::system_error:
+    //     thread::join failed: Resource deadlock would occur
+}
+
+void CallbackBase::wait() {
+    std::unique_lock<std::mutex> lock(mMutex);
+    mCondition.wait(lock, [this]{return mNotified;});
+    join_thread_locked();
+}
+
+bool CallbackBase::on_finish(std::function<bool(void)> post_work) {
+    std::lock_guard<std::mutex> lock(mMutex);
+    if (mPostWork != nullptr) {
+        LOG(ERROR) << "CallbackBase::on_finish -- a post-work function has already been bound to "
+                   "this callback object";
+        return false;
+    }
+    if (post_work == nullptr) {
+        LOG(ERROR) << "CallbackBase::on_finish -- the new post-work function is invalid";
+        return false;
+    }
+    mPostWork = std::move(post_work);
+    return true;
+}
+
+bool CallbackBase::bind_thread(std::thread&& asyncThread) {
+    std::lock_guard<std::mutex> lock(mMutex);
+    if (mThread.joinable()) {
+        LOG(ERROR) << "CallbackBase::bind_thread -- a thread has already been bound to this "
+                   "callback object";
+        return false;
+    }
+    if (!asyncThread.joinable()) {
+        LOG(ERROR) << "CallbackBase::bind_thread -- the new thread is not joinable";
+        return false;
+    }
+    mThread = std::move(asyncThread);
+    return true;
+}
+
+void CallbackBase::join_thread() {
+    std::lock_guard<std::mutex> lock(mMutex);
+    join_thread_locked();
+}
+
+void CallbackBase::notify() {
+    {
+        std::lock_guard<std::mutex> lock(mMutex);
+        mNotified = true;
+        if (mPostWork != nullptr) {
+            bool success = mPostWork();
+            if (!success) {
+                LOG(ERROR) << "CallbackBase::notify -- post work failed";
+            }
+        }
+    }
+    mCondition.notify_all();
+}
+
+void CallbackBase::join_thread_locked() {
+    if (mThread.joinable()) {
+        mThread.join();
+    }
+}
+
+PreparedModelCallback::PreparedModelCallback() :
+        mErrorStatus(ErrorStatus::GENERAL_FAILURE), mPreparedModel(nullptr) {}
+
+PreparedModelCallback::~PreparedModelCallback() {}
+
+Return<void> PreparedModelCallback::notify(ErrorStatus errorStatus,
+                                           const sp<IPreparedModel>& preparedModel) {
+    mErrorStatus = errorStatus;
+    mPreparedModel = preparedModel;
+    CallbackBase::notify();
+    return Void();
+}
+
+ErrorStatus PreparedModelCallback::getStatus() {
+    wait();
+    return mErrorStatus;
+}
+
+sp<IPreparedModel> PreparedModelCallback::getPreparedModel() {
+    wait();
+    return mPreparedModel;
+}
+
+ExecutionCallback::ExecutionCallback() : mErrorStatus(ErrorStatus::GENERAL_FAILURE) {}
+
+ExecutionCallback::~ExecutionCallback() {}
+
+Return<void> ExecutionCallback::notify(ErrorStatus errorStatus) {
+    mErrorStatus = errorStatus;
+    CallbackBase::notify();
+    return Void();
+}
+
+ErrorStatus ExecutionCallback::getStatus() {
+    wait();
+    return mErrorStatus;
+}
+
+}  // namespace implementation
+}  // namespace V1_0
+}  // namespace neuralnetworks
+}  // namespace hardware
+}  // namespace android
diff --git a/neuralnetworks/1.0/vts/functional/Callbacks.h b/neuralnetworks/1.0/vts/functional/Callbacks.h
new file mode 100644
index 0000000..0e2ffb3
--- /dev/null
+++ b/neuralnetworks/1.0/vts/functional/Callbacks.h
@@ -0,0 +1,319 @@
+#ifndef ANDROID_HARDWARE_NEURALNETWORKS_V1_0_CALLBACKS_H
+#define ANDROID_HARDWARE_NEURALNETWORKS_V1_0_CALLBACKS_H
+
+#include <android/hardware/neuralnetworks/1.0/IExecutionCallback.h>
+#include <android/hardware/neuralnetworks/1.0/IPreparedModelCallback.h>
+#include <chrono>
+#include <condition_variable>
+#include <functional>
+#include <hidl/MQDescriptor.h>
+#include <hidl/Status.h>
+#include <mutex>
+#include <thread>
+
+namespace android {
+namespace hardware {
+namespace neuralnetworks {
+namespace V1_0 {
+namespace implementation {
+
+using ::android::hardware::hidl_array;
+using ::android::hardware::hidl_memory;
+using ::android::hardware::hidl_string;
+using ::android::hardware::hidl_vec;
+using ::android::hardware::Return;
+using ::android::hardware::Void;
+using ::android::sp;
+
+/**
+ * The CallbackBase class is used internally by the NeuralNetworks runtime to
+ * synchronize between different threads. An asynchronous task is launched
+ * paired with a callback object. When a client thread requires the output being
+ * generated by the asynchronous task, the client thread can wait for the result
+ * and be blocked until it has completed or a timeout condition has been
+ * reached. Any wait* may safely be called concurrently, even on the same
+ * callback object. When the asynchronous task has finished its workload, it
+ * must immediately call "notify". If the asynchronous task has failed to launch,
+ * the function that tried to launch the asynchronous task must immediately call
+ * "notify". This "notify" call awakens any client threads waiting on the
+ * callback object.
+ *
+ * callback object. When the asynchronous task has finished its workload or has
+ * failed to launch, it must immediately call "notify", awakening any client
+ * threads waiting on the callback object.
+ *
+ * The CallbackBase class implements some of the base synchronization common to
+ * both PrepareModelCallback and ExecutionCallback. For consistency, any HIDL
+ * callback class must inherit from CallbackBase as well as the HIDL callback
+ * interface it implements.
+ *
+ * This class exists to enable synchronization across HIDL. When synchronization
+ * is only required in the same process, consider using std::future, std::mutex,
+ * std::condition_variable, or std::experimental::latch instead.
+ */
+class CallbackBase {
+ public:
+    CallbackBase();
+    ~CallbackBase();
+
+    /**
+     * CallbackBase::wait blocks until notify has been called on the callback
+     * object.
+     */
+    void wait();
+
+    /**
+     * CallbackBase::wait_for blocks until notify has been called on the
+     * callback object or the time duration from the time the wait_for function
+     * was called has expired, whichever comes first.
+     *
+     * @return Status std::cv_status::no_timeout if the callback was notified
+     *                before the time duration expired, std::cv_status::timeout
+     *                otherwise.
+     */
+    template<class Rep, class Period>
+    std::cv_status wait_for(const std::chrono::duration<Rep,Period>& timeout_duration);
+
+    /**
+     * CallbackBase::on_finish binds a function to the callback object. This
+     * bound function will be executed when CallbackBase::notify is called,
+     * before any calls to wait* return. (Note that CallbackBase::wait_for can
+     * return std::cv_status::timeout before CallbackBase::notify is called for
+     * the first time, and hence before the bound function is executed.)
+     *
+     * The bound function must not synchronize with or otherwise access the
+     * callback object it is bound to, as this could cause a deadlock.
+     *
+     * CallbackBase::on_finish can be called at most once on a given callback
+     * object, and the call to CallbackBase::on_finish must finish before
+     * CallbackBase::notify is called.
+     *
+     * @param post_work Function to be invoked the first time
+     *                  CallbackBase::notify is called. Must have a target --
+     *                  i.e., must not compare equal to nullptr. post_work
+     *                  returns true if it successfully completes, false if it
+     *                  fails.
+     * @return bool True if the function was successfully bound, false if
+     *              unsuccessful.
+     *
+     * TODO: Why does the return value of the callback matter?
+     */
+    bool on_finish(std::function<bool(void)> post_work);
+
+    /**
+     * CallbackBase::bind_thread binds a thread to the event for later use by
+     * CallbackBase::join_thread.
+     *
+     * The thread must be passed using std::move.
+     *
+     * Once a thread is bound with CallbackBase::bind_thread, the client code
+     * should ensure that one of the following occurs before the event is
+     * destroyed:
+     * - CallbackBase::join_thread has been called.
+     * - CallbackBase::wait has been called.
+     * - CallbackBase::wait_for has been called and returned other than
+     *   std::cv_status::no_timeout.
+     *
+     * The bound thread shall not call any CallbackBase method with the
+     * exception of CallbackBase::notify, which it must call when the thread has
+     * finished its computation.
+     *
+     * CallbackBase::bind_thread can be called at most once on a given callback
+     * object.
+     *
+     * @param asyncThread Thread to be bound to the callback object. The thread
+     *                    object must represent a thread of execution -- i.e.,
+     *                    asyncThread.joinable() must be true.
+     * @return bool True if successful, false if thread was not properly bound.
+     */
+    bool bind_thread(std::thread&& asyncThread);
+
+    /**
+     * CallbackBase::join_thread ensures that the thread (if any) bound to this
+     * event with CallbackBase::bind_thread has fully finished and cleaned its
+     * resources. It is legal to call this function multiple times, concurrently
+     * or sequentially.
+     */
+    void join_thread();
+
+ protected:
+    /**
+     * CallbackBase::notify enables all prior and future wait* calls on the
+     * callback object to proceed. The call to CallbackBase::notify happens
+     * before any wait* calls on this callback object return (except in the case
+     * of wait_for timing out). The asynchronous call the callback object is
+     * paired with must ensure that any update to state that should be visible
+     * to the caller of wait* happens before the call to CallbackBase::notify.
+     *
+     * CallbackBase::notify must be called exactly once on a given callback
+     * object.
+     */
+    void notify();
+
+ private:
+    // Same as CallbackBase::join_thread but assumes we already hold a lock on
+    // mMutex.
+    void join_thread_locked();
+
+    bool                      mNotified;
+    std::mutex                mMutex;
+    std::condition_variable   mCondition;
+    std::function<bool(void)> mPostWork;
+    std::thread               mThread;
+};
+
+/**
+ * The PreparedModelCallback class is used to receive the error status of
+ * preparing a model as well as the prepared model from a task executing
+ * asynchronously with respect to the runtime. If a calling thread calls wait*
+ * or get* on a PreparedModelCallback object and the corresponding asynchronous
+ * task has not finished preparing the model, the calling thread will block
+ * until the asynchronous task has called notify. For more information on the
+ * synchronization behavior, refer to the CallbackBase class.
+ *
+ * This class inherits the basic blocking and signaling calls from
+ * CallbackBase, and implements the HIDL notify call from
+ * IPreparedModelCallback. This callback object is passed as an argument to
+ * IDevice::prepareModel.
+ */
+class PreparedModelCallback : public CallbackBase, public IPreparedModelCallback {
+ public:
+    PreparedModelCallback();
+    ~PreparedModelCallback() override;
+
+    /**
+     * IPreparedModelCallback::notify marks the callback object with the return
+     * status of the asynchronous model preparation along with the prepared
+     * model, and calls CallbackBase::notify, enabling all prior and future
+     * wait* calls on the PreparedModelCallback object to proceed. For more
+     * information on the synchronization behavior, refer to the CallbackBase
+     * class.
+     *
+     * IPreparedModelCallback::notify must be called exactly once on a given
+     * PreparedModelCallback object.
+     *
+     * @param status Error status returned from asynchronously preparing the
+     *               model; will be:
+     *               - NONE if the asynchronous preparation was successful
+     *               - DEVICE_UNAVAILABLE if driver is offline or busy
+     *               - GENERAL_FAILURE if there is an unspecified error
+     *               - INVALID_ARGUMENT if the input model is invalid
+     * @param preparedModel Returned model that has been prepared for execution,
+     *                      nullptr if the model was unable to be prepared.
+     */
+    Return<void> notify(ErrorStatus status, const sp<IPreparedModel>& preparedModel) override;
+
+    /**
+     * Retrieves the error status returned from the asynchronous task launched
+     * by IDevice::prepareModel. If IDevice::prepareModel has not finished
+     * asynchronously preparing the model, this call will block until the
+     * asynchronous task notifies the object.
+     *
+     * @return status Error status returned from asynchronously preparing the
+     *                model; will be:
+     *                - NONE if the asynchronous preparation was successful
+     *                - DEVICE_UNAVAILABLE if driver is offline or busy
+     *                - GENERAL_FAILURE if there is an unspecified error
+     *                - INVALID_ARGUMENT if the input model is invalid
+     */
+    ErrorStatus getStatus();
+
+    /**
+     * Retrieves the model that has been prepared for execution from the
+     * asynchronous task launched by IDevice::prepareModel. If
+     * IDevice::prepareModel has not finished asynchronously preparing the
+     * model, this call will block until the asynchronous task notifies the
+     * object.
+     *
+     * @return preparedModel Returned model that has been prepared for
+     *                       execution, nullptr if the model was unable to be
+     *                       prepared.
+     */
+    sp<IPreparedModel> getPreparedModel();
+
+ private:
+    ErrorStatus        mErrorStatus;
+    sp<IPreparedModel> mPreparedModel;
+};
+
+/**
+ * The ExecutionCallback class is used to receive the error status of the
+ * execution from a task executing asynchronously with respect to the runtime.
+ * If a calling thread calls wait* or get* on a PreparedModelCallback object and
+ * the corresponding asynchronous task has not finished the execution, the
+ * calling thread will block until the asynchronous task has called notify. For
+ * more information on the synchronization behavior, refer to the CallbackBase
+ * class.
+ *
+ * This class inherits the basic blocking and signaling calls from
+ * CallbackBase, and implements the HIDL notify call from
+ * IExecutionCallback. This callback object is passed as an argument to
+ * IPreparedModel::execute.
+ */
+class ExecutionCallback : public CallbackBase,  public IExecutionCallback {
+ public:
+    ExecutionCallback();
+    ~ExecutionCallback() override;
+
+    /**
+     * IExecutionCallback::notify marks the callback object with the return
+     * status of the asynchronous execution that held this callback and enables
+     * all prior and future wait* calls on the ExecutionCallback object to
+     * proceed. For more information on the synchronization behavior, refer to
+     * the CallbackBase class.
+     *
+     * IExecutionCallback::notify must be called exactly once on a given
+     * ExecutionCallback object.
+     *
+     * @param status Error status returned from asynchronously preparing the
+     *               model; will be:
+     *               - NONE if the asynchronous execution was successful
+     *               - DEVICE_UNAVAILABLE if driver is offline or busy
+     *               - GENERAL_FAILURE if there is an unspecified error
+     *               - OUTPUT_INSUFFICIENT_SIZE if provided output buffer is
+     *                 not large enough to store the resultant values
+     *               - INVALID_ARGUMENT if the input request is invalid
+     */
+    Return<void> notify(ErrorStatus status) override;
+
+    /**
+     * Retrieves the error status returned from the asynchronous task launched
+     * by IPreparedModel::execute. If IPreparedModel::execute has not finished
+     * asynchronously executing, this call will block until the asynchronous task
+     * notifies the object.
+     *
+     * @return status Error status returned from asynchronously preparing the
+     *                model; will be:
+     *                - NONE if the asynchronous execution was successful
+     *                - DEVICE_UNAVAILABLE if driver is offline or busy
+     *                - GENERAL_FAILURE if there is an unspecified error
+     *                - OUTPUT_INSUFFICIENT_SIZE if provided output buffer is
+     *                  not large enough to store the resultant values
+     *                - INVALID_ARGUMENT if the input request is invalid
+     */
+    ErrorStatus getStatus();
+
+ private:
+    ErrorStatus mErrorStatus;
+};
+
+
+// template function implementation(s) below this point
+
+template<class Rep, class Period>
+std::cv_status CallbackBase::wait_for(const std::chrono::duration<Rep,Period>& timeout_duration) {
+    std::unique_lock<std::mutex> lock(mMutex);
+    std::cv_status status = mCondition.wait_for(lock, timeout_duration, [this]{return mNotified;});
+    if (status != std::cv_status::timeout) {
+        join_thread_locked();
+    }
+    return status;
+}
+
+}  // namespace implementation
+}  // namespace V1_0
+}  // namespace neuralnetworks
+}  // namespace hardware
+}  // namespace android
+
+#endif  // ANDROID_HARDWARE_NEURALNETWORKS_V1_0_CALLBACKS_H
diff --git a/neuralnetworks/1.0/vts/functional/Event.cpp b/neuralnetworks/1.0/vts/functional/Event.cpp
deleted file mode 100644
index efaacb3..0000000
--- a/neuralnetworks/1.0/vts/functional/Event.cpp
+++ /dev/null
@@ -1,94 +0,0 @@
-#include "Event.h"
-#include <android-base/logging.h>
-
-namespace android {
-namespace hardware {
-namespace neuralnetworks {
-namespace V1_0 {
-namespace implementation {
-
-Event::Event() : mStatus(Status::WAITING) {}
-
-Event::~Event() {
-    // Note that we cannot call Event::join_thread from here: Event is
-    // intended to be reference counted, and it is possible that the
-    // reference count drops to zero in the bound thread, causing the
-    // bound thread to call this destructor. If a thread tries to join
-    // itself, it throws an exception, producing a message like the
-    // following:
-    //
-    //     terminating with uncaught exception of type std::__1::system_error:
-    //     thread::join failed: Resource deadlock would occur
-}
-
-Return<void> Event::notify(ErrorStatus status) {
-    {
-        std::lock_guard<std::mutex> lock(mMutex);
-        mStatus = status == ErrorStatus::NONE ? Status::SUCCESS : Status::ERROR;
-        if (mStatus == Status::SUCCESS && mCallback != nullptr) {
-            bool success = mCallback();
-            if (!success) {
-                LOG(ERROR) << "Event::notify -- callback failed";
-            }
-        }
-    }
-    mCondition.notify_all();
-    return Void();
-}
-
-Event::Status Event::poll() {
-    std::lock_guard<std::mutex> lock(mMutex);
-    return mStatus;
-}
-
-Event::Status Event::wait() {
-    std::unique_lock<std::mutex> lock(mMutex);
-    mCondition.wait(lock, [this]{return mStatus != Status::WAITING;});
-    join_thread_locked();
-    return mStatus;
-}
-
-bool Event::on_finish(std::function<bool(void)> callback) {
-    std::lock_guard<std::mutex> lock(mMutex);
-    if (mCallback != nullptr) {
-        LOG(ERROR) << "Event::on_finish -- a callback has already been bound to this event";
-        return false;
-    }
-    if (callback == nullptr) {
-        LOG(ERROR) << "Event::on_finish -- the new callback is invalid";
-        return false;
-    }
-    mCallback = std::move(callback);
-    return true;
-}
-
-bool Event::bind_thread(std::thread&& asyncThread) {
-    std::lock_guard<std::mutex> lock(mMutex);
-    if (mThread.joinable()) {
-        LOG(ERROR) << "Event::bind_thread -- a thread has already been bound to this event";
-        return false;
-    }
-    if (!asyncThread.joinable()) {
-        LOG(ERROR) << "Event::bind_thread -- the new thread is not joinable";
-        return false;
-    }
-    mThread = std::move(asyncThread);
-    return true;
-}
-
-void Event::join_thread() {
-    std::lock_guard<std::mutex> lock(mMutex);
-    join_thread_locked();
-}
-
-void Event::join_thread_locked() {
-    if (mThread.joinable()) {
-        mThread.join();
-    }
-}
-
-}  // namespace implementation
-}  // namespace V1_0
-}  // namespace neuralnetworks
-}  // namespace hardware
-}  // namespace android
diff --git a/neuralnetworks/1.0/vts/functional/Event.h b/neuralnetworks/1.0/vts/functional/Event.h
deleted file mode 100644
index 7dd4070..0000000
--- a/neuralnetworks/1.0/vts/functional/Event.h
+++ /dev/null
@@ -1,216 +0,0 @@
-#ifndef ANDROID_HARDWARE_NEURALNETWORKS_V1_0_EVENT_H
-#define ANDROID_HARDWARE_NEURALNETWORKS_V1_0_EVENT_H
-
-#include <android/hardware/neuralnetworks/1.0/IEvent.h>
-#include <chrono>
-#include <condition_variable>
-#include <functional>
-#include <hidl/MQDescriptor.h>
-#include <hidl/Status.h>
-#include <mutex>
-#include <thread>
-
-namespace android {
-namespace hardware {
-namespace neuralnetworks {
-namespace V1_0 {
-namespace implementation {
-
-using ::android::hardware::hidl_array;
-using ::android::hardware::hidl_memory;
-using ::android::hardware::hidl_string;
-using ::android::hardware::hidl_vec;
-using ::android::hardware::Return;
-using ::android::hardware::Void;
-using ::android::sp;
-
-/**
- * The Event class is used internally by the Neuralnetworks runtime to
- * synchronize between different threads. An asynchronous task is launched
- * paired with an event object. When a client thread requires the output being
- * processed by the asynchronous task, the client thread can wait for the result
- * and be blocked until it has completed or a timeout condition has been
- * reached, or poll the result periodically. Both poll and wait* may safely be
- * called concurrently, even on the same event. When the server thread has
- * completed, it should immediately call "notify" to indicate the corresponding
- * output has been produced and awaken any client threads waiting on the event.
- *
- * This class exists to enable synchronization across HIDL. When synchronization
- * is only required in the same process, consider using std::future, std::mutex,
- * std::condition_variable, or std::experimental::latch instead.
- */
-struct Event : public IEvent {
-    Event();
-    ~Event() override;
-
-    /**
-     * Event::Status::WAITING -- The corresponding asynchronous execution has
-     *                           not yet finished.
-     * Event::Status::SUCCESS -- The corresponding asynchronous execution has
-     *                           succeeded and the output is ready to be
-     *                           consumed.
-     * Event::Status::TIMEOUT -- The calling thread has waited longer than the
-     *                           user has specified. This only applies to the
-     *                           methods Event::wait_for and Event::wait_until.
-     * Event::Status::ERROR   -- The corresponding asynchronous execution has
-     *                           failed to properly execute.
-     */
-    enum class Status : uint32_t {
-        WAITING,
-        SUCCESS,
-        TIMEOUT,
-        ERROR,
-    };
-
-    /**
-     * IEvent::notify marks the event with the return status of the
-     * asynchronous call the event is paired with and enables all
-     * prior and future wait calls on the Event object to proceed. The
-     * call to IEvent::notify happens before any wait* calls on
-     * this event return (except in the case of TIMEOUT) and before
-     * any poll calls that see the resulting status. The asynchronous
-     * call the event is paired with must ensure that any update to
-     * state that should be visible to the caller of wait* or poll
-     * happens before the call to IEvent::notify.
-     *
-     * IEvent::notify can be called at most once on a given event.
-     *
-     * @param neuralnetworks::V1_0::ErrorStatus ErrorStatus::NONE on success
-     */
-    Return<void> notify(ErrorStatus status) override;
-
-    /**
-     * Event::poll returns the current status of the event.
-     *
-     * @return Status SUCCESS, ERROR, or WAITING
-     */
-    Event::Status poll();
-
-    /**
-     * Event::wait blocks until the event has been signaled.
-     *
-     * @return Status SUCCESS or ERROR
-     */
-    Event::Status wait();
-
-    /**
-     * Event::wait_for blocks until the event has been signaled or the time
-     * duration from the time the wait_for function was called has expired,
-     * whichever comes first.
-     *
-     * @return Status SUCCESS, ERROR, or TIMEOUT
-     */
-    template<class Rep, class Period>
-    Event::Status wait_for(const std::chrono::duration<Rep,Period>& timeout_duration);
-
-    /**
-     * Event::wait_until blocks until the event has been signaled or a certain
-     * time has been reached, whichever comes first.
-     *
-     * @return Status SUCCESS, ERROR, or TIMEOUT
-     */
-    template<class Clock, class Duration>
-    Event::Status wait_until(const std::chrono::time_point<Clock,Duration>& timeout_duration);
-
-    /**
-     * Event::on_finish binds a callback function to the event. The
-     * callback will be executed when IEvent::notify is called, before
-     * any calls to wait* return. (Note that wait_for or wait_until
-     * can return TIMEOUT before IEvent::notify is called for the
-     * first time, and hence before the callback is executed.)
-     *
-     * The callback function must not synchronize with or otherwise
-     * access the event object it is bound to.
-     *
-     * Event::on_finish can be called at most once on a given event.
-     *
-     * @param callback Function to be invoked the first time IEvent::notify is
-     *                 called. Must have a target -- i.e., must not compare equal
-     *                 to nullptr. Callback returns true if it successfully
-     *                 completes, false if it fails.
-     * @return bool True if the callback was successfully bound, false if
-     *              unsuccessful.
-     *
-     * TODO: What if notify has already been called before on_finish?
-     * TODO: Why does the return value of the callback matter?
-     */
-    bool on_finish(std::function<bool(void)> callback);
-
-    /**
-     * Event::bind_thread binds a thread to the event for later use by
-     * Event::join_thread.
-     *
-     * The thread must be passed using std::move.
-     *
-     * Once a thread is bound with Event::bind_thread, the client code
-     * should ensure that one of the following occurs before the event is
-     * destroyed:
-     * - Event::join_thread has been called.
-     * - Event::wait has been called.
-     * - Event::wait_for has been called and returned other than TIMEOUT.
-     * - Event::wait_until has been called and returned other than TIMEOUT.
-     *
-     * The bound thread shall not call any Event method with the exception of
-     * IEvent::notify, which it will call when the thread has finished its
-     * computation.
-     *
-     * Event::bind_thread can be called at most once on a given event.
-     *
-     * @param asyncThread Thread to be bound to the event. The thread object
-     *                    must represent a thread of execution -- i.e.,
-     *                    asyncThread.joinable() must be true.
-     * @return bool True if successful, false if thread was not properly bound.
-     */
-    bool bind_thread(std::thread&& asyncThread);
-
-    /**
-     * Event::join_thread ensures that the thread (if any) bound to
-     * this event with Event::bind_thread has fully finished and
-     * cleaned its resources. It is legal to call this function
-     * multiple times, concurrently or sequentially.
-     */
-    void join_thread();
-
- private:
-    // Same as Event::join_thread but assumes we already hold a lock on mMutex.
-    void join_thread_locked();
-
-    Status                    mStatus;
-    std::mutex                mMutex;
-    std::condition_variable   mCondition;
-    std::function<bool(void)> mCallback;
-    std::thread               mThread;
-};
-
-
-// template function implementations
-
-template<class Rep, class Period>
-Event::Status Event::wait_for(const std::chrono::duration<Rep,Period>& timeout_duration) {
-    std::unique_lock<std::mutex> lock(mMutex);
-    std::cv_status status = mCondition.wait_for(lock, timeout_duration,
-                                                [this]{return mStatus != Status::WAITING;});
-    if (status != std::cv_status::timeout) {
-        join_thread_locked();
-    }
-    return status != std::cv_status::timeout ? mStatus : Status::TIMEOUT;
-}
-
-template<class Clock, class Duration>
-Event::Status Event::wait_until(const std::chrono::time_point<Clock,Duration>& timeout_time) {
-    std::unique_lock<std::mutex> lock(mMutex);
-    std::cv_status status = mCondition.wait_until(lock, timeout_time,
-                                                  [this]{return mStatus != Status::WAITING;});
-    if (status != std::cv_status::timeout) {
-        join_thread_locked();
-    }
-    return status != std::cv_status::timeout ? mStatus : Status::TIMEOUT;
-}
-
-}  // namespace implementation
-}  // namespace V1_0
-}  // namespace neuralnetworks
-}  // namespace hardware
-}  // namespace android
-
-#endif  // ANDROID_HARDWARE_NEURALNETWORKS_V1_0_EVENT_H
diff --git a/neuralnetworks/1.0/vts/functional/GeneratedTestHarness.cpp b/neuralnetworks/1.0/vts/functional/GeneratedTestHarness.cpp
index 4b8daec..366bfc1 100644
--- a/neuralnetworks/1.0/vts/functional/GeneratedTestHarness.cpp
+++ b/neuralnetworks/1.0/vts/functional/GeneratedTestHarness.cpp
@@ -14,7 +14,7 @@
  * limitations under the License.
  */
 
-#include "Event.h"
+#include "Callbacks.h"
 #include "TestHarness.h"
 #include "VtsHalNeuralnetworksV1_0TargetTest.h"
 
@@ -32,7 +32,8 @@
 hidl_memory allocateSharedMemory(int64_t size, const std::string& type = "ashmem");
 
 namespace generated_tests {
-using ::android::hardware::neuralnetworks::V1_0::implementation::Event;
+using ::android::hardware::neuralnetworks::V1_0::implementation::ExecutionCallback;
+using ::android::hardware::neuralnetworks::V1_0::implementation::PreparedModelCallback;
 using ::generated_tests::filter;
 using ::generated_tests::for_all;
 using ::generated_tests::for_each;
@@ -65,22 +66,22 @@
 void Execute(const sp<IDevice>& device, std::function<Model(void)> create_model,
              std::function<bool(int)> is_ignored,
              const std::vector<MixedTypedExampleType>& examples) {
-    Model model = create_model();
-    sp<IPreparedModel> preparedModel;
-    sp<Event> preparationEvent = new Event();
-    ASSERT_NE(nullptr, preparationEvent.get());
-    Return<void> prepareRet = device->prepareModel(
-        model, preparationEvent, [&](ErrorStatus status, const sp<IPreparedModel>& prepared) {
-            EXPECT_EQ(ErrorStatus::NONE, status);
-            preparedModel = prepared;
-        });
-    ASSERT_TRUE(prepareRet.isOk());
-    ASSERT_NE(nullptr, preparedModel.get());
-    Event::Status preparationStatus = preparationEvent->wait();
-    EXPECT_EQ(Event::Status::SUCCESS, preparationStatus);
-
     const uint32_t INPUT = 0;
     const uint32_t OUTPUT = 1;
+    Model model = create_model();
+
+    // launch prepare model
+    sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
+    ASSERT_NE(nullptr, preparedModelCallback.get());
+    Return<ErrorStatus> prepareLaunchStatus = device->prepareModel(model, preparedModelCallback);
+    ASSERT_TRUE(prepareLaunchStatus.isOk());
+
+    // retrieve prepared model
+    preparedModelCallback->wait();
+    ErrorStatus prepareReturnStatus = preparedModelCallback->getStatus();
+    EXPECT_EQ(ErrorStatus::NONE, prepareReturnStatus);
+    sp<IPreparedModel> preparedModel = preparedModelCallback->getPreparedModel();
+    ASSERT_NE(nullptr, preparedModel.get());
 
     int example_no = 1;
     for (auto& example : examples) {
@@ -160,15 +161,19 @@
 
         inputMemory->commit();
         outputMemory->commit();
-        // execute request
-        sp<Event> executionEvent = new Event();
-        ASSERT_NE(nullptr, executionEvent.get());
-        Return<ErrorStatus> executeStatus = preparedModel->execute(
-            {.inputs = inputs_info, .outputs = outputs_info, .pools = pools}, executionEvent);
-        ASSERT_TRUE(executeStatus.isOk());
-        EXPECT_EQ(ErrorStatus::NONE, static_cast<ErrorStatus>(executeStatus));
-        Event::Status eventStatus = executionEvent->wait();
-        EXPECT_EQ(Event::Status::SUCCESS, eventStatus);
+
+        // launch execution
+        sp<ExecutionCallback> executionCallback = new ExecutionCallback();
+        ASSERT_NE(nullptr, executionCallback.get());
+        Return<ErrorStatus> executionLaunchStatus = preparedModel->execute(
+            {.inputs = inputs_info, .outputs = outputs_info, .pools = pools}, executionCallback);
+        ASSERT_TRUE(executionLaunchStatus.isOk());
+        EXPECT_EQ(ErrorStatus::NONE, static_cast<ErrorStatus>(executionLaunchStatus));
+
+        // retrieve execution status
+        executionCallback->wait();
+        ErrorStatus executionReturnStatus = executionCallback->getStatus();
+        EXPECT_EQ(ErrorStatus::NONE, executionReturnStatus);
 
         // validate results
         outputMemory->read();
diff --git a/neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworksV1_0TargetTest.cpp b/neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworksV1_0TargetTest.cpp
index 0f354d1..b99e20e 100644
--- a/neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworksV1_0TargetTest.cpp
+++ b/neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworksV1_0TargetTest.cpp
@@ -17,7 +17,8 @@
 #define LOG_TAG "neuralnetworks_hidl_hal_test"
 
 #include "VtsHalNeuralnetworksV1_0TargetTest.h"
-#include "Event.h"
+
+#include "Callbacks.h"
 #include "Models.h"
 #include "TestHarness.h"
 
@@ -32,8 +33,10 @@
 namespace vts {
 namespace functional {
 
-using ::android::hardware::neuralnetworks::V1_0::implementation::Event;
+using ::android::hardware::neuralnetworks::V1_0::implementation::ExecutionCallback;
+using ::android::hardware::neuralnetworks::V1_0::implementation::PreparedModelCallback;
 using ::generated_tests::MixedTypedExampleType;
+
 namespace generated_tests {
 extern void Execute(const sp<IDevice>&, std::function<Model(void)>, std::function<bool(int)>,
                     const std::vector<MixedTypedExampleType>&);
@@ -66,26 +69,22 @@
 
 void NeuralnetworksHidlTest::TearDown() {}
 
-sp<IPreparedModel> NeuralnetworksHidlTest::doPrepareModelShortcut(const Model& model) {
-    sp<IPreparedModel> preparedModel;
-    ErrorStatus prepareStatus;
-    sp<Event> preparationEvent = new Event();
-    if (preparationEvent.get() == nullptr) {
+sp<IPreparedModel> NeuralnetworksHidlTest::doPrepareModelShortcut() {
+    Model model = createValidTestModel();
+
+    sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
+    if (preparedModelCallback == nullptr) {
+        return nullptr;
+    }
+    Return<ErrorStatus> prepareLaunchStatus = device->prepareModel(model, preparedModelCallback);
+    if (!prepareLaunchStatus.isOk() || prepareLaunchStatus != ErrorStatus::NONE) {
         return nullptr;
     }
 
-    Return<void> prepareRet = device->prepareModel(
-        model, preparationEvent, [&](ErrorStatus status, const sp<IPreparedModel>& prepared) {
-            prepareStatus = status;
-            preparedModel = prepared;
-        });
-
-    if (!prepareRet.isOk() || prepareStatus != ErrorStatus::NONE ||
-        preparedModel.get() == nullptr) {
-        return nullptr;
-    }
-    Event::Status eventStatus = preparationEvent->wait();
-    if (eventStatus != Event::Status::SUCCESS) {
+    preparedModelCallback->wait();
+    ErrorStatus prepareReturnStatus = preparedModelCallback->getStatus();
+    sp<IPreparedModel> preparedModel = preparedModelCallback->getPreparedModel();
+    if (prepareReturnStatus != ErrorStatus::NONE || preparedModel == nullptr) {
         return nullptr;
     }
 
@@ -151,99 +150,121 @@
 // prepare simple model positive test
 TEST_F(NeuralnetworksHidlTest, SimplePrepareModelPositiveTest) {
     Model model = createValidTestModel();
-    sp<Event> preparationEvent = new Event();
-    ASSERT_NE(nullptr, preparationEvent.get());
-    Return<void> prepareRet = device->prepareModel(
-        model, preparationEvent, [&](ErrorStatus status, const sp<IPreparedModel>& prepared) {
-            EXPECT_EQ(ErrorStatus::NONE, status);
-            (void)prepared;
-        });
-    ASSERT_TRUE(prepareRet.isOk());
+    sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
+    ASSERT_NE(nullptr, preparedModelCallback.get());
+    Return<ErrorStatus> prepareLaunchStatus = device->prepareModel(model, preparedModelCallback);
+    ASSERT_TRUE(prepareLaunchStatus.isOk());
+    EXPECT_EQ(ErrorStatus::NONE, static_cast<ErrorStatus>(prepareLaunchStatus));
+
+    preparedModelCallback->wait();
+    ErrorStatus prepareReturnStatus = preparedModelCallback->getStatus();
+    EXPECT_EQ(ErrorStatus::NONE, prepareReturnStatus);
+    sp<IPreparedModel> preparedModel = preparedModelCallback->getPreparedModel();
+    EXPECT_NE(nullptr, preparedModel.get());
 }
 
 // prepare simple model negative test 1
 TEST_F(NeuralnetworksHidlTest, SimplePrepareModelNegativeTest1) {
     Model model = createInvalidTestModel1();
-    sp<Event> preparationEvent = new Event();
-    ASSERT_NE(nullptr, preparationEvent.get());
-    Return<void> prepareRet = device->prepareModel(
-        model, preparationEvent, [&](ErrorStatus status, const sp<IPreparedModel>& prepared) {
-            EXPECT_EQ(ErrorStatus::INVALID_ARGUMENT, status);
-            (void)prepared;
-        });
-    ASSERT_TRUE(prepareRet.isOk());
+    sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
+    ASSERT_NE(nullptr, preparedModelCallback.get());
+    Return<ErrorStatus> prepareLaunchStatus = device->prepareModel(model, preparedModelCallback);
+    ASSERT_TRUE(prepareLaunchStatus.isOk());
+    EXPECT_EQ(ErrorStatus::INVALID_ARGUMENT, static_cast<ErrorStatus>(prepareLaunchStatus));
+
+    preparedModelCallback->wait();
+    ErrorStatus prepareReturnStatus = preparedModelCallback->getStatus();
+    EXPECT_EQ(ErrorStatus::INVALID_ARGUMENT, prepareReturnStatus);
+    sp<IPreparedModel> preparedModel = preparedModelCallback->getPreparedModel();
+    EXPECT_EQ(nullptr, preparedModel.get());
 }
 
 // prepare simple model negative test 2
 TEST_F(NeuralnetworksHidlTest, SimplePrepareModelNegativeTest2) {
     Model model = createInvalidTestModel2();
-    sp<Event> preparationEvent = new Event();
-    ASSERT_NE(nullptr, preparationEvent.get());
-    Return<void> prepareRet = device->prepareModel(
-        model, preparationEvent, [&](ErrorStatus status, const sp<IPreparedModel>& prepared) {
-            EXPECT_EQ(ErrorStatus::INVALID_ARGUMENT, status);
-            (void)prepared;
-        });
-    ASSERT_TRUE(prepareRet.isOk());
+    sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
+    ASSERT_NE(nullptr, preparedModelCallback.get());
+    Return<ErrorStatus> prepareLaunchStatus = device->prepareModel(model, preparedModelCallback);
+    ASSERT_TRUE(prepareLaunchStatus.isOk());
+    EXPECT_EQ(ErrorStatus::INVALID_ARGUMENT, static_cast<ErrorStatus>(prepareLaunchStatus));
+
+    preparedModelCallback->wait();
+    ErrorStatus prepareReturnStatus = preparedModelCallback->getStatus();
+    EXPECT_EQ(ErrorStatus::INVALID_ARGUMENT, prepareReturnStatus);
+    sp<IPreparedModel> preparedModel = preparedModelCallback->getPreparedModel();
+    EXPECT_EQ(nullptr, preparedModel.get());
 }
 
 // execute simple graph positive test
 TEST_F(NeuralnetworksHidlTest, SimpleExecuteGraphPositiveTest) {
-    Model model = createValidTestModel();
-    sp<IPreparedModel> preparedModel = doPrepareModelShortcut(model);
-    ASSERT_NE(nullptr, preparedModel.get());
-    Request request = createValidTestRequest();
-
-    sp<Event> executionEvent = new Event();
-    ASSERT_NE(nullptr, executionEvent.get());
-    Return<ErrorStatus> executeStatus = preparedModel->execute(request, executionEvent);
-    ASSERT_TRUE(executeStatus.isOk());
-    EXPECT_EQ(ErrorStatus::NONE, static_cast<ErrorStatus>(executeStatus));
-    Event::Status eventStatus = executionEvent->wait();
-    EXPECT_EQ(Event::Status::SUCCESS, eventStatus);
-
     std::vector<float> outputData = {-1.0f, -1.0f, -1.0f, -1.0f};
     std::vector<float> expectedData = {6.0f, 8.0f, 10.0f, 12.0f};
     const uint32_t OUTPUT = 1;
 
-    sp<IMemory> outputMemory = mapMemory(request.pools[OUTPUT]);
-    ASSERT_NE(nullptr, outputMemory.get());
-    float* outputPtr = reinterpret_cast<float*>(static_cast<void*>(outputMemory->getPointer()));
-    ASSERT_NE(nullptr, outputPtr);
-    outputMemory->read();
-    std::copy(outputPtr, outputPtr + outputData.size(), outputData.begin());
-    outputMemory->commit();
+    sp<IPreparedModel> preparedModel = doPrepareModelShortcut();
+    ASSERT_NE(nullptr, preparedModel.get());
+    Request request = createValidTestRequest();
+
+    auto postWork = [&] {
+        sp<IMemory> outputMemory = mapMemory(request.pools[OUTPUT]);
+        if (outputMemory == nullptr) {
+            return false;
+        }
+        float* outputPtr = reinterpret_cast<float*>(static_cast<void*>(outputMemory->getPointer()));
+        if (outputPtr == nullptr) {
+            return false;
+        }
+        outputMemory->read();
+        std::copy(outputPtr, outputPtr + outputData.size(), outputData.begin());
+        outputMemory->commit();
+        return true;
+    };
+
+    sp<ExecutionCallback> executionCallback = new ExecutionCallback();
+    ASSERT_NE(nullptr, executionCallback.get());
+    executionCallback->on_finish(postWork);
+    Return<ErrorStatus> executeLaunchStatus = preparedModel->execute(request, executionCallback);
+    ASSERT_TRUE(executeLaunchStatus.isOk());
+    EXPECT_EQ(ErrorStatus::NONE, static_cast<ErrorStatus>(executeLaunchStatus));
+
+    executionCallback->wait();
+    ErrorStatus executionReturnStatus = executionCallback->getStatus();
+    EXPECT_EQ(ErrorStatus::NONE, executionReturnStatus);
     EXPECT_EQ(expectedData, outputData);
 }
 
 // execute simple graph negative test 1
 TEST_F(NeuralnetworksHidlTest, SimpleExecuteGraphNegativeTest1) {
-    Model model = createValidTestModel();
-    sp<IPreparedModel> preparedModel = doPrepareModelShortcut(model);
+    sp<IPreparedModel> preparedModel = doPrepareModelShortcut();
     ASSERT_NE(nullptr, preparedModel.get());
     Request request = createInvalidTestRequest1();
 
-    sp<Event> executionEvent = new Event();
-    ASSERT_NE(nullptr, executionEvent.get());
-    Return<ErrorStatus> executeStatus = preparedModel->execute(request, executionEvent);
-    ASSERT_TRUE(executeStatus.isOk());
-    EXPECT_EQ(ErrorStatus::INVALID_ARGUMENT, static_cast<ErrorStatus>(executeStatus));
-    executionEvent->wait();
+    sp<ExecutionCallback> executionCallback = new ExecutionCallback();
+    ASSERT_NE(nullptr, executionCallback.get());
+    Return<ErrorStatus> executeLaunchStatus = preparedModel->execute(request, executionCallback);
+    ASSERT_TRUE(executeLaunchStatus.isOk());
+    EXPECT_EQ(ErrorStatus::INVALID_ARGUMENT, static_cast<ErrorStatus>(executeLaunchStatus));
+
+    executionCallback->wait();
+    ErrorStatus executionReturnStatus = executionCallback->getStatus();
+    EXPECT_EQ(ErrorStatus::INVALID_ARGUMENT, executionReturnStatus);
 }
 
 // execute simple graph negative test 2
 TEST_F(NeuralnetworksHidlTest, SimpleExecuteGraphNegativeTest2) {
-    Model model = createValidTestModel();
-    sp<IPreparedModel> preparedModel = doPrepareModelShortcut(model);
+    sp<IPreparedModel> preparedModel = doPrepareModelShortcut();
     ASSERT_NE(nullptr, preparedModel.get());
     Request request = createInvalidTestRequest2();
 
-    sp<Event> executionEvent = new Event();
-    ASSERT_NE(nullptr, executionEvent.get());
-    Return<ErrorStatus> executeStatus = preparedModel->execute(request, executionEvent);
-    ASSERT_TRUE(executeStatus.isOk());
-    EXPECT_EQ(ErrorStatus::INVALID_ARGUMENT, static_cast<ErrorStatus>(executeStatus));
-    executionEvent->wait();
+    sp<ExecutionCallback> executionCallback = new ExecutionCallback();
+    ASSERT_NE(nullptr, executionCallback.get());
+    Return<ErrorStatus> executeLaunchStatus = preparedModel->execute(request, executionCallback);
+    ASSERT_TRUE(executeLaunchStatus.isOk());
+    EXPECT_EQ(ErrorStatus::INVALID_ARGUMENT, static_cast<ErrorStatus>(executeLaunchStatus));
+
+    executionCallback->wait();
+    ErrorStatus executionReturnStatus = executionCallback->getStatus();
+    EXPECT_EQ(ErrorStatus::INVALID_ARGUMENT, executionReturnStatus);
 }
 
 // Mixed-typed examples
diff --git a/neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworksV1_0TargetTest.h b/neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworksV1_0TargetTest.h
index 1b3b334..5cd209a 100644
--- a/neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworksV1_0TargetTest.h
+++ b/neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworksV1_0TargetTest.h
@@ -18,7 +18,9 @@
 #define VTS_HAL_NEURALNETWORKS_V1_0_TARGET_TESTS_H
 
 #include <android/hardware/neuralnetworks/1.0/IDevice.h>
+#include <android/hardware/neuralnetworks/1.0/IExecutionCallback.h>
 #include <android/hardware/neuralnetworks/1.0/IPreparedModel.h>
+#include <android/hardware/neuralnetworks/1.0/IPreparedModelCallback.h>
 #include <android/hardware/neuralnetworks/1.0/types.h>
 #include <android/hidl/allocator/1.0/IAllocator.h>
 
@@ -72,13 +74,28 @@
     void SetUp() override;
     void TearDown() override;
 
-    sp<IPreparedModel> doPrepareModelShortcut(const Model& model);
+    sp<IPreparedModel> doPrepareModelShortcut();
 
     sp<IDevice> device;
 };
 
 }  // namespace functional
 }  // namespace vts
+
+// pretty-print values for error messages
+
+template<typename CharT, typename Traits>
+::std::basic_ostream<CharT, Traits>& operator<<(::std::basic_ostream<CharT, Traits>& os,
+                                                ErrorStatus errorStatus) {
+    return os << toString(errorStatus);
+}
+
+template<typename CharT, typename Traits>
+::std::basic_ostream<CharT, Traits>& operator<<(::std::basic_ostream<CharT, Traits>& os,
+                                                DeviceStatus deviceStatus) {
+    return os << toString(deviceStatus);
+}
+
 }  // namespace V1_0
 }  // namespace neuralnetworks
 }  // namespace hardware