diff --git a/compatibility_matrices/Android.bp b/compatibility_matrices/Android.bp
index 33157a6..9d4e55c 100644
--- a/compatibility_matrices/Android.bp
+++ b/compatibility_matrices/Android.bp
@@ -23,8 +23,9 @@
         "kernel_config_o_3.18",
         "kernel_config_o_4.4",
         "kernel_config_o_4.9",
-    ]
+    ],
 }
+
 vintf_compatibility_matrix {
     name: "framework_compatibility_matrix.1.xml",
     stem: "compatibility_matrix.1.xml",
@@ -35,8 +36,9 @@
         "kernel_config_o_3.18",
         "kernel_config_o_4.4",
         "kernel_config_o_4.9",
-    ]
+    ],
 }
+
 vintf_compatibility_matrix {
     name: "framework_compatibility_matrix.2.xml",
     stem: "compatibility_matrix.2.xml",
@@ -47,7 +49,7 @@
         "kernel_config_o_mr1_3.18",
         "kernel_config_o_mr1_4.4",
         "kernel_config_o_mr1_4.9",
-    ]
+    ],
 }
 
 vintf_compatibility_matrix {
@@ -60,7 +62,7 @@
         "kernel_config_p_4.4",
         "kernel_config_p_4.9",
         "kernel_config_p_4.14",
-    ]
+    ],
 }
 
 vintf_compatibility_matrix {
@@ -73,7 +75,20 @@
         "kernel_config_q_4.9",
         "kernel_config_q_4.14",
         "kernel_config_q_4.19",
-    ]
+    ],
+}
+
+vintf_compatibility_matrix {
+    name: "framework_compatibility_matrix.5.xml",
+    stem: "compatibility_matrix.5.xml",
+    srcs: [
+        "compatibility_matrix.5.xml",
+    ],
+    kernel_configs: [
+        "kernel_config_r_4.14",
+        "kernel_config_r_4.19",
+        "kernel_config_r_5.4",
+    ],
 }
 
 vintf_compatibility_matrix {
@@ -83,8 +98,8 @@
         "compatibility_matrix.current.xml",
     ],
     kernel_configs: [
-        "kernel_config_r_4.14",
-        "kernel_config_r_4.19",
-        "kernel_config_r_5.4",
-    ]
+        "kernel_config_current_4.14",
+        "kernel_config_current_4.19",
+        "kernel_config_current_5.4",
+    ],
 }
diff --git a/compatibility_matrices/Android.mk b/compatibility_matrices/Android.mk
index 6d204cb..96191c8 100644
--- a/compatibility_matrices/Android.mk
+++ b/compatibility_matrices/Android.mk
@@ -97,6 +97,7 @@
     framework_compatibility_matrix.2.xml \
     framework_compatibility_matrix.3.xml \
     framework_compatibility_matrix.4.xml \
+    framework_compatibility_matrix.5.xml \
     framework_compatibility_matrix.current.xml \
     framework_compatibility_matrix.device.xml \
 
diff --git a/compatibility_matrices/compatibility_matrix.5.xml b/compatibility_matrices/compatibility_matrix.5.xml
new file mode 100644
index 0000000..cc4f0cd
--- /dev/null
+++ b/compatibility_matrices/compatibility_matrix.5.xml
@@ -0,0 +1,521 @@
+<compatibility-matrix version="1.0" type="framework" level="5">
+    <hal format="hidl" optional="true">
+        <name>android.hardware.atrace</name>
+        <version>1.0</version>
+        <interface>
+            <name>IAtraceDevice</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="false">
+        <name>android.hardware.audio</name>
+        <version>6.0</version>
+        <interface>
+            <name>IDevicesFactory</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="false">
+        <name>android.hardware.audio.effect</name>
+        <version>6.0</version>
+        <interface>
+            <name>IEffectsFactory</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.authsecret</name>
+        <version>1.0</version>
+        <interface>
+            <name>IAuthSecret</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.automotive.audiocontrol</name>
+        <version>1.0</version>
+        <interface>
+            <name>IAudioControl</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.automotive.evs</name>
+        <version>1.0</version>
+        <interface>
+            <name>IEvsEnumerator</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.automotive.vehicle</name>
+        <version>2.0</version>
+        <interface>
+            <name>IVehicle</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.biometrics.face</name>
+        <version>1.0</version>
+        <interface>
+            <name>IBiometricsFace</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.biometrics.fingerprint</name>
+        <version>2.1</version>
+        <interface>
+            <name>IBiometricsFingerprint</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.bluetooth</name>
+        <version>1.0-1</version>
+        <interface>
+            <name>IBluetoothHci</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.bluetooth.audio</name>
+        <version>2.0</version>
+        <interface>
+            <name>IBluetoothAudioProvidersFactory</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.boot</name>
+        <version>1.1</version>
+        <interface>
+            <name>IBootControl</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.broadcastradio</name>
+        <version>1.0-1</version>
+        <interface>
+            <name>IBroadcastRadioFactory</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.broadcastradio</name>
+        <version>2.0</version>
+        <interface>
+            <name>IBroadcastRadio</name>
+            <regex-instance>.*</regex-instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.camera.provider</name>
+        <version>2.4-5</version>
+        <interface>
+            <name>ICameraProvider</name>
+            <regex-instance>[^/]+/[0-9]+</regex-instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.cas</name>
+        <version>1.1</version>
+        <interface>
+            <name>IMediaCasService</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.configstore</name>
+        <version>1.1</version>
+        <interface>
+            <name>ISurfaceFlingerConfigs</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.confirmationui</name>
+        <version>1.0</version>
+        <interface>
+            <name>IConfirmationUI</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.contexthub</name>
+        <version>1.0</version>
+        <interface>
+            <name>IContexthub</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.drm</name>
+        <version>1.0-2</version>
+        <interface>
+            <name>ICryptoFactory</name>
+            <regex-instance>.*</regex-instance>
+        </interface>
+        <interface>
+            <name>IDrmFactory</name>
+            <regex-instance>.*</regex-instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.dumpstate</name>
+        <version>1.1</version>
+        <interface>
+            <name>IDumpstateDevice</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="false">
+        <name>android.hardware.gatekeeper</name>
+        <version>1.0</version>
+        <interface>
+            <name>IGatekeeper</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.gnss</name>
+        <version>2.0</version>
+        <interface>
+            <name>IGnss</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="false">
+        <name>android.hardware.graphics.allocator</name>
+        <version>2.0</version>
+        <version>3.0</version>
+        <interface>
+            <name>IAllocator</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="false">
+        <name>android.hardware.graphics.composer</name>
+        <version>2.1-3</version>
+        <interface>
+            <name>IComposer</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="false">
+        <name>android.hardware.graphics.mapper</name>
+        <version>2.1</version>
+        <version>3.0</version>
+        <interface>
+            <name>IMapper</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="false">
+        <name>android.hardware.health</name>
+        <version>2.1</version>
+        <interface>
+            <name>IHealth</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.health.storage</name>
+        <version>1.0</version>
+        <interface>
+            <name>IStorage</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="aidl" optional="true">
+        <name>android.hardware.identity</name>
+        <interface>
+            <name>IIdentityCredentialStore</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.ir</name>
+        <version>1.0</version>
+        <interface>
+            <name>IConsumerIr</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.input.classifier</name>
+        <version>1.0</version>
+        <interface>
+            <name>IInputClassifier</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="false">
+        <name>android.hardware.keymaster</name>
+        <version>3.0</version>
+        <version>4.0-1</version>
+        <interface>
+            <name>IKeymasterDevice</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.keymaster</name>
+        <version>4.0-1</version>
+        <interface>
+            <name>IKeymasterDevice</name>
+            <instance>strongbox</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.light</name>
+        <version>2.0</version>
+        <interface>
+            <name>ILight</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="aidl" optional="true">
+        <name>android.hardware.light</name>
+        <interface>
+            <name>ILights</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.media.c2</name>
+        <version>1.0</version>
+        <interface>
+            <name>IComponentStore</name>
+            <regex-instance>default[0-9]*</regex-instance>
+            <regex-instance>vendor[0-9]*_software</regex-instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.media.omx</name>
+        <version>1.0</version>
+        <interface>
+            <name>IOmx</name>
+            <instance>default</instance>
+        </interface>
+        <interface>
+            <name>IOmxStore</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.memtrack</name>
+        <version>1.0</version>
+        <interface>
+            <name>IMemtrack</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.neuralnetworks</name>
+        <version>1.0-3</version>
+        <interface>
+            <name>IDevice</name>
+            <regex-instance>.*</regex-instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.nfc</name>
+        <version>1.2</version>
+        <interface>
+            <name>INfc</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.oemlock</name>
+        <version>1.0</version>
+        <interface>
+            <name>IOemLock</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="aidl" optional="false">
+        <name>android.hardware.power</name>
+        <interface>
+            <name>IPower</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.power.stats</name>
+        <version>1.0</version>
+        <interface>
+            <name>IPowerStats</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.radio</name>
+        <version>1.5</version>
+        <interface>
+            <name>IRadio</name>
+            <instance>slot1</instance>
+            <instance>slot2</instance>
+            <instance>slot3</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.radio</name>
+        <version>1.2</version>
+        <interface>
+            <name>ISap</name>
+            <instance>slot1</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.radio.config</name>
+        <!--
+        See compatibility_matrix.4.xml on versioning of radio config HAL.
+        -->
+        <version>1.1</version>
+        <interface>
+            <name>IRadioConfig</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.renderscript</name>
+        <version>1.0</version>
+        <interface>
+            <name>IDevice</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.secure_element</name>
+        <version>1.0-2</version>
+        <interface>
+            <name>ISecureElement</name>
+            <regex-instance>eSE[1-9][0-9]*</regex-instance>
+            <regex-instance>SIM[1-9][0-9]*</regex-instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.sensors</name>
+        <version>1.0</version>
+        <version>2.0</version>
+        <interface>
+            <name>ISensors</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.soundtrigger</name>
+        <version>2.0-2</version>
+        <interface>
+            <name>ISoundTriggerHw</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.tetheroffload.config</name>
+        <version>1.0</version>
+        <interface>
+            <name>IOffloadConfig</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.tetheroffload.control</name>
+        <version>1.0</version>
+        <interface>
+            <name>IOffloadControl</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.thermal</name>
+        <version>2.0</version>
+        <interface>
+            <name>IThermal</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.tv.cec</name>
+        <version>1.0</version>
+        <interface>
+            <name>IHdmiCec</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.tv.input</name>
+        <version>1.0</version>
+        <interface>
+            <name>ITvInput</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.usb</name>
+        <version>1.0-2</version>
+        <interface>
+            <name>IUsb</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.usb.gadget</name>
+        <version>1.0</version>
+        <interface>
+            <name>IUsbGadget</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="aidl" optional="true">
+        <name>android.hardware.vibrator</name>
+        <interface>
+            <name>IVibrator</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.vr</name>
+        <version>1.0</version>
+        <interface>
+            <name>IVr</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.weaver</name>
+        <version>1.0</version>
+        <interface>
+            <name>IWeaver</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.wifi</name>
+        <version>1.0-3</version>
+        <interface>
+            <name>IWifi</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.wifi.hostapd</name>
+        <version>1.0-1</version>
+        <interface>
+            <name>IHostapd</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+    <hal format="hidl" optional="true">
+        <name>android.hardware.wifi.supplicant</name>
+        <version>1.0-2</version>
+        <interface>
+            <name>ISupplicant</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+</compatibility-matrix>
diff --git a/compatibility_matrices/compatibility_matrix.current.xml b/compatibility_matrices/compatibility_matrix.current.xml
index cc4f0cd..3e39ab7 100644
--- a/compatibility_matrices/compatibility_matrix.current.xml
+++ b/compatibility_matrices/compatibility_matrix.current.xml
@@ -1,4 +1,4 @@
-<compatibility-matrix version="1.0" type="framework" level="5">
+<compatibility-matrix version="1.0" type="framework" level="6">
     <hal format="hidl" optional="true">
         <name>android.hardware.atrace</name>
         <version>1.0</version>
@@ -128,14 +128,6 @@
         </interface>
     </hal>
     <hal format="hidl" optional="true">
-        <name>android.hardware.configstore</name>
-        <version>1.1</version>
-        <interface>
-            <name>ISurfaceFlingerConfigs</name>
-            <instance>default</instance>
-        </interface>
-    </hal>
-    <hal format="hidl" optional="true">
         <name>android.hardware.confirmationui</name>
         <version>1.0</version>
         <interface>
diff --git a/keymaster/4.1/default/Android.bp b/keymaster/4.1/default/Android.bp
index 27297b9..3442b18 100644
--- a/keymaster/4.1/default/Android.bp
+++ b/keymaster/4.1/default/Android.bp
@@ -20,6 +20,7 @@
     relative_install_path: "hw",
     vendor: true,
     init_rc: ["android.hardware.keymaster@4.1-service.rc"],
+    vintf_fragments: ["android.hardware.keymaster@4.1-service.xml"],
     srcs: ["service.cpp"],
 
     shared_libs: [
diff --git a/keymaster/4.1/default/android.hardware.keymaster@4.1-service.xml b/keymaster/4.1/default/android.hardware.keymaster@4.1-service.xml
new file mode 100644
index 0000000..9ba05c5
--- /dev/null
+++ b/keymaster/4.1/default/android.hardware.keymaster@4.1-service.xml
@@ -0,0 +1,11 @@
+<manifest version="1.0" type="device">
+    <hal format="hidl">
+        <name>android.hardware.keymaster</name>
+        <transport>hwbinder</transport>
+        <version>4.1</version>
+        <interface>
+            <name>IKeymasterDevice</name>
+            <instance>default</instance>
+        </interface>
+    </hal>
+</manifest>
diff --git a/neuralnetworks/1.0/vts/functional/GeneratedTestHarness.cpp b/neuralnetworks/1.0/vts/functional/GeneratedTestHarness.cpp
index e28605d..ae1e3a2 100644
--- a/neuralnetworks/1.0/vts/functional/GeneratedTestHarness.cpp
+++ b/neuralnetworks/1.0/vts/functional/GeneratedTestHarness.cpp
@@ -125,7 +125,9 @@
 // Test driver for those generated from ml/nn/runtime/test/spec
 void Execute(const sp<IDevice>& device, const TestModel& testModel) {
     const Model model = createModel(testModel);
-    const Request request = createRequest(testModel);
+
+    ExecutionContext context;
+    const Request request = context.createRequest(testModel);
 
     // Create IPreparedModel.
     sp<IPreparedModel> preparedModel;
@@ -143,7 +145,7 @@
     ASSERT_EQ(ErrorStatus::NONE, executionCallback->getStatus());
 
     // Retrieve execution results.
-    const std::vector<TestBuffer> outputs = getOutputBuffers(request);
+    const std::vector<TestBuffer> outputs = context.getOutputBuffers(request);
 
     // We want "close-enough" results.
     checkResults(testModel, outputs);
@@ -158,6 +160,10 @@
     return TestModelManager::get().getTestModels(filter);
 }
 
+std::vector<NamedModel> getNamedModels(const FilterNameFn& filter) {
+    return TestModelManager::get().getTestModels(filter);
+}
+
 std::string printGeneratedTest(const testing::TestParamInfo<GeneratedTestParam>& info) {
     const auto& [namedDevice, namedModel] = info.param;
     return gtestCompliantName(getName(namedDevice) + "_" + getName(namedModel));
diff --git a/neuralnetworks/1.0/vts/functional/GeneratedTestHarness.h b/neuralnetworks/1.0/vts/functional/GeneratedTestHarness.h
index f230a02..1a55c2f 100644
--- a/neuralnetworks/1.0/vts/functional/GeneratedTestHarness.h
+++ b/neuralnetworks/1.0/vts/functional/GeneratedTestHarness.h
@@ -37,6 +37,9 @@
 using FilterFn = std::function<bool(const test_helper::TestModel&)>;
 std::vector<NamedModel> getNamedModels(const FilterFn& filter);
 
+using FilterNameFn = std::function<bool(const std::string&)>;
+std::vector<NamedModel> getNamedModels(const FilterNameFn& filter);
+
 std::string printGeneratedTest(const testing::TestParamInfo<GeneratedTestParam>& info);
 
 #define INSTANTIATE_GENERATED_TEST(TestSuite, filter)                                     \
diff --git a/neuralnetworks/1.0/vts/functional/Utils.cpp b/neuralnetworks/1.0/vts/functional/Utils.cpp
index 0dba85a..3613e69 100644
--- a/neuralnetworks/1.0/vts/functional/Utils.cpp
+++ b/neuralnetworks/1.0/vts/functional/Utils.cpp
@@ -21,10 +21,13 @@
 
 #include <android-base/logging.h>
 #include <android/hardware/neuralnetworks/1.0/types.h>
+#include <android/hardware_buffer.h>
 #include <android/hidl/allocator/1.0/IAllocator.h>
 #include <android/hidl/memory/1.0/IMemory.h>
 #include <hidlmemory/mapping.h>
+#include <vndk/hardware_buffer.h>
 
+#include <gtest/gtest.h>
 #include <algorithm>
 #include <iostream>
 #include <vector>
@@ -37,10 +40,64 @@
 using V1_0::Request;
 using V1_0::RequestArgument;
 
-constexpr uint32_t kInputPoolIndex = 0;
-constexpr uint32_t kOutputPoolIndex = 1;
+std::unique_ptr<TestAshmem> TestAshmem::create(uint32_t size) {
+    auto ashmem = std::make_unique<TestAshmem>(size);
+    return ashmem->mIsValid ? std::move(ashmem) : nullptr;
+}
 
-Request createRequest(const TestModel& testModel) {
+void TestAshmem::initialize(uint32_t size) {
+    mIsValid = false;
+    ASSERT_GT(size, 0);
+    mHidlMemory = nn::allocateSharedMemory(size);
+    ASSERT_TRUE(mHidlMemory.valid());
+    mMappedMemory = mapMemory(mHidlMemory);
+    ASSERT_NE(mMappedMemory, nullptr);
+    mPtr = static_cast<uint8_t*>(static_cast<void*>(mMappedMemory->getPointer()));
+    ASSERT_NE(mPtr, nullptr);
+    mIsValid = true;
+}
+
+std::unique_ptr<TestBlobAHWB> TestBlobAHWB::create(uint32_t size) {
+    auto ahwb = std::make_unique<TestBlobAHWB>(size);
+    return ahwb->mIsValid ? std::move(ahwb) : nullptr;
+}
+
+void TestBlobAHWB::initialize(uint32_t size) {
+    mIsValid = false;
+    ASSERT_GT(size, 0);
+    const auto usage = AHARDWAREBUFFER_USAGE_CPU_READ_OFTEN | AHARDWAREBUFFER_USAGE_CPU_WRITE_OFTEN;
+    const AHardwareBuffer_Desc desc = {
+            .width = size,
+            .height = 1,
+            .layers = 1,
+            .format = AHARDWAREBUFFER_FORMAT_BLOB,
+            .usage = usage,
+            .stride = size,
+    };
+    ASSERT_EQ(AHardwareBuffer_allocate(&desc, &mAhwb), 0);
+    ASSERT_NE(mAhwb, nullptr);
+
+    void* buffer = nullptr;
+    ASSERT_EQ(AHardwareBuffer_lock(mAhwb, usage, -1, nullptr, &buffer), 0);
+    ASSERT_NE(buffer, nullptr);
+    mPtr = static_cast<uint8_t*>(buffer);
+
+    const native_handle_t* handle = AHardwareBuffer_getNativeHandle(mAhwb);
+    ASSERT_NE(handle, nullptr);
+    mHidlMemory = hidl_memory("hardware_buffer_blob", handle, desc.width);
+    mIsValid = true;
+}
+
+TestBlobAHWB::~TestBlobAHWB() {
+    if (mAhwb) {
+        AHardwareBuffer_unlock(mAhwb, nullptr);
+        AHardwareBuffer_release(mAhwb);
+    }
+}
+
+Request ExecutionContext::createRequest(const TestModel& testModel, MemoryType memoryType) {
+    CHECK(memoryType == MemoryType::ASHMEM || memoryType == MemoryType::BLOB_AHWB);
+
     // Model inputs.
     hidl_vec<RequestArgument> inputs(testModel.main.inputIndexes.size());
     size_t inputSize = 0;
@@ -80,16 +137,19 @@
     }
 
     // Allocate memory pools.
-    hidl_vec<hidl_memory> pools = {nn::allocateSharedMemory(inputSize),
-                                   nn::allocateSharedMemory(outputSize)};
-    CHECK_NE(pools[kInputPoolIndex].size(), 0u);
-    CHECK_NE(pools[kOutputPoolIndex].size(), 0u);
-    sp<IMemory> inputMemory = mapMemory(pools[kInputPoolIndex]);
-    CHECK(inputMemory.get() != nullptr);
-    uint8_t* inputPtr = static_cast<uint8_t*>(static_cast<void*>(inputMemory->getPointer()));
-    CHECK(inputPtr != nullptr);
+    if (memoryType == MemoryType::ASHMEM) {
+        mInputMemory = TestAshmem::create(inputSize);
+        mOutputMemory = TestAshmem::create(outputSize);
+    } else {
+        mInputMemory = TestBlobAHWB::create(inputSize);
+        mOutputMemory = TestBlobAHWB::create(outputSize);
+    }
+    EXPECT_NE(mInputMemory, nullptr);
+    EXPECT_NE(mOutputMemory, nullptr);
+    hidl_vec<hidl_memory> pools = {mInputMemory->getHidlMemory(), mOutputMemory->getHidlMemory()};
 
     // Copy input data to the memory pool.
+    uint8_t* inputPtr = mInputMemory->getPointer();
     for (uint32_t i = 0; i < testModel.main.inputIndexes.size(); i++) {
         const auto& op = testModel.main.operands[testModel.main.inputIndexes[i]];
         if (op.data.size() > 0) {
@@ -102,18 +162,13 @@
     return {.inputs = std::move(inputs), .outputs = std::move(outputs), .pools = std::move(pools)};
 }
 
-std::vector<TestBuffer> getOutputBuffers(const Request& request) {
-    sp<IMemory> outputMemory = mapMemory(request.pools[kOutputPoolIndex]);
-    CHECK(outputMemory.get() != nullptr);
-    uint8_t* outputPtr = static_cast<uint8_t*>(static_cast<void*>(outputMemory->getPointer()));
-    CHECK(outputPtr != nullptr);
-
+std::vector<TestBuffer> ExecutionContext::getOutputBuffers(const Request& request) const {
     // Copy out output results.
+    uint8_t* outputPtr = mOutputMemory->getPointer();
     std::vector<TestBuffer> outputBuffers;
     for (const auto& output : request.outputs) {
         outputBuffers.emplace_back(output.location.length, outputPtr + output.location.offset);
     }
-
     return outputBuffers;
 }
 
diff --git a/neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworks.cpp b/neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworks.cpp
index cb22250..2c17796 100644
--- a/neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworks.cpp
+++ b/neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworks.cpp
@@ -129,11 +129,17 @@
 
 TEST_P(ValidationTest, Test) {
     const Model model = createModel(kTestModel);
-    const Request request = createRequest(kTestModel);
+    ExecutionContext context;
+    const Request request = context.createRequest(kTestModel);
     ASSERT_FALSE(kTestModel.expectFailure);
     validateEverything(kDevice, model, request);
 }
 
-INSTANTIATE_GENERATED_TEST(ValidationTest, [](const test_helper::TestModel&) { return true; });
+INSTANTIATE_GENERATED_TEST(ValidationTest, [](const std::string& testName) {
+    // Skip validation for the "inputs_as_internal" and "all_tensors_as_inputs"
+    // generated tests.
+    return testName.find("inputs_as_internal") == std::string::npos &&
+           testName.find("all_tensors_as_inputs") == std::string::npos;
+});
 
 }  // namespace android::hardware::neuralnetworks::V1_0::vts::functional
diff --git a/neuralnetworks/1.0/vts/functional/include/1.0/Utils.h b/neuralnetworks/1.0/vts/functional/include/1.0/Utils.h
index 6d4534c..3292f79 100644
--- a/neuralnetworks/1.0/vts/functional/include/1.0/Utils.h
+++ b/neuralnetworks/1.0/vts/functional/include/1.0/Utils.h
@@ -19,6 +19,8 @@
 
 #include <android-base/logging.h>
 #include <android/hardware/neuralnetworks/1.0/types.h>
+#include <android/hardware_buffer.h>
+#include <android/hidl/memory/1.0/IMemory.h>
 #include <algorithm>
 #include <iosfwd>
 #include <string>
@@ -28,11 +30,73 @@
 
 namespace android::hardware::neuralnetworks {
 
-// Create HIDL Request from the TestModel struct.
-V1_0::Request createRequest(const test_helper::TestModel& testModel);
+// Convenience class to manage the lifetime of memory resources.
+class TestMemoryBase {
+    DISALLOW_COPY_AND_ASSIGN(TestMemoryBase);
 
-// After execution, copy out output results from the output memory pool.
-std::vector<::test_helper::TestBuffer> getOutputBuffers(const V1_0::Request& request);
+  public:
+    TestMemoryBase() = default;
+    virtual ~TestMemoryBase() = default;
+    uint8_t* getPointer() const { return mPtr; }
+    hidl_memory getHidlMemory() const { return mHidlMemory; }
+
+  protected:
+    uint8_t* mPtr = nullptr;
+    hidl_memory mHidlMemory;
+    bool mIsValid = false;
+};
+
+class TestAshmem : public TestMemoryBase {
+  public:
+    static std::unique_ptr<TestAshmem> create(uint32_t size);
+
+    // Prefer TestAshmem::create.
+    // The constructor calls initialize, which constructs the memory resources. This is a workaround
+    // that gtest macros cannot be used directly in a constructor.
+    TestAshmem(uint32_t size) { initialize(size); }
+
+  private:
+    void initialize(uint32_t size);
+    sp<hidl::memory::V1_0::IMemory> mMappedMemory;
+};
+
+class TestBlobAHWB : public TestMemoryBase {
+  public:
+    static std::unique_ptr<TestBlobAHWB> create(uint32_t size);
+
+    // Prefer TestBlobAHWB::create.
+    // The constructor calls initialize, which constructs the memory resources. This is a
+    // workaround that gtest macros cannot be used directly in a constructor.
+    TestBlobAHWB(uint32_t size) { initialize(size); }
+    ~TestBlobAHWB();
+
+  private:
+    void initialize(uint32_t size);
+    AHardwareBuffer* mAhwb = nullptr;
+};
+
+enum class MemoryType { ASHMEM, BLOB_AHWB, DEVICE };
+
+// Manages the lifetime of memory resources used in an execution.
+class ExecutionContext {
+    DISALLOW_COPY_AND_ASSIGN(ExecutionContext);
+
+  public:
+    static constexpr uint32_t kInputPoolIndex = 0;
+    static constexpr uint32_t kOutputPoolIndex = 1;
+
+    ExecutionContext() = default;
+
+    // Create HIDL Request from the TestModel struct.
+    V1_0::Request createRequest(const test_helper::TestModel& testModel,
+                                MemoryType memoryType = MemoryType::ASHMEM);
+
+    // After execution, copy out output results from the output memory pool.
+    std::vector<test_helper::TestBuffer> getOutputBuffers(const V1_0::Request& request) const;
+
+  private:
+    std::unique_ptr<TestMemoryBase> mInputMemory, mOutputMemory;
+};
 
 // Delete element from hidl_vec. hidl_vec doesn't support a "remove" operation,
 // so this is efficiently accomplished by moving the element to the end and
diff --git a/neuralnetworks/1.1/vts/functional/GeneratedTestHarness.cpp b/neuralnetworks/1.1/vts/functional/GeneratedTestHarness.cpp
index cee15a3..a233835 100644
--- a/neuralnetworks/1.1/vts/functional/GeneratedTestHarness.cpp
+++ b/neuralnetworks/1.1/vts/functional/GeneratedTestHarness.cpp
@@ -133,7 +133,9 @@
 // Test driver for those generated from ml/nn/runtime/test/spec
 void Execute(const sp<IDevice>& device, const TestModel& testModel) {
     const Model model = createModel(testModel);
-    const Request request = createRequest(testModel);
+
+    ExecutionContext context;
+    const Request request = context.createRequest(testModel);
 
     // Create IPreparedModel.
     sp<IPreparedModel> preparedModel;
@@ -151,7 +153,7 @@
     ASSERT_EQ(ErrorStatus::NONE, executionCallback->getStatus());
 
     // Retrieve execution results.
-    const std::vector<TestBuffer> outputs = getOutputBuffers(request);
+    const std::vector<TestBuffer> outputs = context.getOutputBuffers(request);
 
     // We want "close-enough" results.
     checkResults(testModel, outputs);
@@ -166,6 +168,10 @@
     return TestModelManager::get().getTestModels(filter);
 }
 
+std::vector<NamedModel> getNamedModels(const FilterNameFn& filter) {
+    return TestModelManager::get().getTestModels(filter);
+}
+
 std::string printGeneratedTest(const testing::TestParamInfo<GeneratedTestParam>& info) {
     const auto& [namedDevice, namedModel] = info.param;
     return gtestCompliantName(getName(namedDevice) + "_" + getName(namedModel));
diff --git a/neuralnetworks/1.1/vts/functional/GeneratedTestHarness.h b/neuralnetworks/1.1/vts/functional/GeneratedTestHarness.h
index cf449ea..4b1a96e 100644
--- a/neuralnetworks/1.1/vts/functional/GeneratedTestHarness.h
+++ b/neuralnetworks/1.1/vts/functional/GeneratedTestHarness.h
@@ -37,6 +37,9 @@
 using FilterFn = std::function<bool(const test_helper::TestModel&)>;
 std::vector<NamedModel> getNamedModels(const FilterFn& filter);
 
+using FilterNameFn = std::function<bool(const std::string&)>;
+std::vector<NamedModel> getNamedModels(const FilterNameFn& filter);
+
 std::string printGeneratedTest(const testing::TestParamInfo<GeneratedTestParam>& info);
 
 #define INSTANTIATE_GENERATED_TEST(TestSuite, filter)                                     \
diff --git a/neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworks.cpp b/neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworks.cpp
index d56d40b..54e8802 100644
--- a/neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworks.cpp
+++ b/neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworks.cpp
@@ -132,11 +132,17 @@
 
 TEST_P(ValidationTest, Test) {
     const Model model = createModel(kTestModel);
-    const Request request = createRequest(kTestModel);
+    ExecutionContext context;
+    const Request request = context.createRequest(kTestModel);
     ASSERT_FALSE(kTestModel.expectFailure);
     validateEverything(kDevice, model, request);
 }
 
-INSTANTIATE_GENERATED_TEST(ValidationTest, [](const test_helper::TestModel&) { return true; });
+INSTANTIATE_GENERATED_TEST(ValidationTest, [](const std::string& testName) {
+    // Skip validation for the "inputs_as_internal" and "all_tensors_as_inputs"
+    // generated tests.
+    return testName.find("inputs_as_internal") == std::string::npos &&
+           testName.find("all_tensors_as_inputs") == std::string::npos;
+});
 
 }  // namespace android::hardware::neuralnetworks::V1_1::vts::functional
diff --git a/neuralnetworks/1.2/vts/functional/GeneratedTestHarness.cpp b/neuralnetworks/1.2/vts/functional/GeneratedTestHarness.cpp
index 3ab0135..35275b4 100644
--- a/neuralnetworks/1.2/vts/functional/GeneratedTestHarness.cpp
+++ b/neuralnetworks/1.2/vts/functional/GeneratedTestHarness.cpp
@@ -68,6 +68,7 @@
     Executor executor;
     MeasureTiming measureTiming;
     OutputType outputType;
+    MemoryType memoryType;
 };
 
 }  // namespace
@@ -216,7 +217,8 @@
         return;
     }
 
-    Request request = createRequest(testModel);
+    ExecutionContext context;
+    Request request = context.createRequest(testModel, testConfig.memoryType);
     if (testConfig.outputType == OutputType::INSUFFICIENT) {
         makeOutputInsufficientSize(/*outputIndex=*/0, &request);
     }
@@ -326,7 +328,7 @@
     }
 
     // Retrieve execution results.
-    const std::vector<TestBuffer> outputs = getOutputBuffers(request);
+    const std::vector<TestBuffer> outputs = context.getOutputBuffers(request);
 
     // We want "close-enough" results.
     checkResults(testModel, outputs);
@@ -337,24 +339,30 @@
     std::vector<OutputType> outputTypesList;
     std::vector<MeasureTiming> measureTimingList;
     std::vector<Executor> executorList;
+    std::vector<MemoryType> memoryTypeList;
 
     if (testDynamicOutputShape) {
         outputTypesList = {OutputType::UNSPECIFIED, OutputType::INSUFFICIENT};
         measureTimingList = {MeasureTiming::NO, MeasureTiming::YES};
         executorList = {Executor::ASYNC, Executor::SYNC, Executor::BURST};
+        memoryTypeList = {MemoryType::ASHMEM};
     } else {
         outputTypesList = {OutputType::FULLY_SPECIFIED};
         measureTimingList = {MeasureTiming::NO, MeasureTiming::YES};
         executorList = {Executor::ASYNC, Executor::SYNC, Executor::BURST};
+        memoryTypeList = {MemoryType::ASHMEM, MemoryType::BLOB_AHWB};
     }
 
     for (const OutputType outputType : outputTypesList) {
         for (const MeasureTiming measureTiming : measureTimingList) {
             for (const Executor executor : executorList) {
-                const TestConfig testConfig = {.executor = executor,
-                                               .measureTiming = measureTiming,
-                                               .outputType = outputType};
-                EvaluatePreparedModel(preparedModel, testModel, testConfig);
+                for (const MemoryType memoryType : memoryTypeList) {
+                    const TestConfig testConfig = {.executor = executor,
+                                                   .measureTiming = measureTiming,
+                                                   .outputType = outputType,
+                                                   .memoryType = memoryType};
+                    EvaluatePreparedModel(preparedModel, testModel, testConfig);
+                }
             }
         }
     }
@@ -382,6 +390,10 @@
     return TestModelManager::get().getTestModels(filter);
 }
 
+std::vector<NamedModel> getNamedModels(const FilterNameFn& filter) {
+    return TestModelManager::get().getTestModels(filter);
+}
+
 std::string printGeneratedTest(const testing::TestParamInfo<GeneratedTestParam>& info) {
     const auto& [namedDevice, namedModel] = info.param;
     return gtestCompliantName(getName(namedDevice) + "_" + getName(namedModel));
diff --git a/neuralnetworks/1.2/vts/functional/GeneratedTestHarness.h b/neuralnetworks/1.2/vts/functional/GeneratedTestHarness.h
index dfc980c..98295ff 100644
--- a/neuralnetworks/1.2/vts/functional/GeneratedTestHarness.h
+++ b/neuralnetworks/1.2/vts/functional/GeneratedTestHarness.h
@@ -41,6 +41,9 @@
 using FilterFn = std::function<bool(const test_helper::TestModel&)>;
 std::vector<NamedModel> getNamedModels(const FilterFn& filter);
 
+using FilterNameFn = std::function<bool(const std::string&)>;
+std::vector<NamedModel> getNamedModels(const FilterNameFn& filter);
+
 std::string printGeneratedTest(const testing::TestParamInfo<GeneratedTestParam>& info);
 
 #define INSTANTIATE_GENERATED_TEST(TestSuite, filter)                                     \
diff --git a/neuralnetworks/1.2/vts/functional/VtsHalNeuralnetworks.cpp b/neuralnetworks/1.2/vts/functional/VtsHalNeuralnetworks.cpp
index 4fbd0e2..a60ec4d 100644
--- a/neuralnetworks/1.2/vts/functional/VtsHalNeuralnetworks.cpp
+++ b/neuralnetworks/1.2/vts/functional/VtsHalNeuralnetworks.cpp
@@ -153,7 +153,8 @@
 
 TEST_P(ValidationTest, Test) {
     const Model model = createModel(kTestModel);
-    const Request request = createRequest(kTestModel);
+    ExecutionContext context;
+    const Request request = context.createRequest(kTestModel);
     if (kTestModel.expectFailure) {
         validateFailure(kDevice, model, request);
     } else {
@@ -161,7 +162,12 @@
     }
 }
 
-INSTANTIATE_GENERATED_TEST(ValidationTest, [](const test_helper::TestModel&) { return true; });
+INSTANTIATE_GENERATED_TEST(ValidationTest, [](const std::string& testName) {
+    // Skip validation for the "inputs_as_internal" and "all_tensors_as_inputs"
+    // generated tests.
+    return testName.find("inputs_as_internal") == std::string::npos &&
+           testName.find("all_tensors_as_inputs") == std::string::npos;
+});
 
 sp<IPreparedModel> getPreparedModel_1_2(const sp<implementation::PreparedModelCallback>& callback) {
     sp<V1_0::IPreparedModel> preparedModelV1_0 = callback->getPreparedModel();
diff --git a/neuralnetworks/1.3/vts/functional/Android.bp b/neuralnetworks/1.3/vts/functional/Android.bp
index f936267..545a5be 100644
--- a/neuralnetworks/1.3/vts/functional/Android.bp
+++ b/neuralnetworks/1.3/vts/functional/Android.bp
@@ -40,6 +40,7 @@
         "BasicTests.cpp",
         "CompilationCachingTests.cpp",
         "GeneratedTestHarness.cpp",
+        "MemoryDomainTests.cpp",
         "QualityOfServiceTests.cpp",
         "TestAssertions.cpp",
         "ValidateBurst.cpp",
diff --git a/neuralnetworks/1.3/vts/functional/GeneratedTestHarness.cpp b/neuralnetworks/1.3/vts/functional/GeneratedTestHarness.cpp
index 5689a39..4dbac16 100644
--- a/neuralnetworks/1.3/vts/functional/GeneratedTestHarness.cpp
+++ b/neuralnetworks/1.3/vts/functional/GeneratedTestHarness.cpp
@@ -72,21 +72,10 @@
 
 namespace {
 
-enum class Executor { ASYNC, SYNC, BURST, FENCED };
-
 enum class OutputType { FULLY_SPECIFIED, UNSPECIFIED, INSUFFICIENT, MISSED_DEADLINE };
 
-enum class MemoryType { SHARED, DEVICE };
-
 enum class IOType { INPUT, OUTPUT };
 
-static void waitForSyncFence(int syncFd) {
-    constexpr int kInfiniteTimeout = -1;
-    ASSERT_GT(syncFd, 0);
-    int r = sync_wait(syncFd, kInfiniteTimeout);
-    ASSERT_GE(r, 0);
-}
-
 struct TestConfig {
     Executor executor;
     MeasureTiming measureTiming;
@@ -277,6 +266,13 @@
 
 }  // namespace
 
+void waitForSyncFence(int syncFd) {
+    constexpr int kInfiniteTimeout = -1;
+    ASSERT_GT(syncFd, 0);
+    int r = sync_wait(syncFd, kInfiniteTimeout);
+    ASSERT_GE(r, 0);
+}
+
 Model createModel(const TestModel& testModel) {
     uint32_t constCopySize = 0;
     uint32_t constRefSize = 0;
@@ -338,21 +334,39 @@
     }
 }
 
-constexpr uint32_t kInputPoolIndex = 0;
-constexpr uint32_t kOutputPoolIndex = 1;
-constexpr uint32_t kDeviceMemoryBeginIndex = 2;
+class ExecutionContextV1_3 {
+  public:
+    ExecutionContextV1_3(sp<IDevice> device, sp<IPreparedModel> preparedModel)
+        : kDevice(std::move(device)), kPreparedModel(std::move(preparedModel)) {}
 
-static std::pair<Request, std::vector<sp<IBuffer>>> createRequest(
-        const sp<IDevice>& device, const sp<IPreparedModel>& preparedModel,
-        const TestModel& testModel, bool preferDeviceMemory) {
+    std::optional<Request> createRequest(const TestModel& testModel, MemoryType memoryType);
+    std::vector<TestBuffer> getOutputBuffers(const TestModel& testModel,
+                                             const Request& request) const;
+
+  private:
+    // Get a TestBuffer with data copied from an IBuffer object.
+    void getBuffer(const sp<IBuffer>& buffer, size_t size, TestBuffer* testBuffer) const;
+
+    static constexpr uint32_t kInputPoolIndex = 0;
+    static constexpr uint32_t kOutputPoolIndex = 1;
+    static constexpr uint32_t kDeviceMemoryBeginIndex = 2;
+
+    const sp<IDevice> kDevice;
+    const sp<IPreparedModel> kPreparedModel;
+    std::unique_ptr<TestMemoryBase> mInputMemory, mOutputMemory;
+    std::vector<sp<IBuffer>> mBuffers;
+};
+
+std::optional<Request> ExecutionContextV1_3::createRequest(const TestModel& testModel,
+                                                           MemoryType memoryType) {
     // Memory pools are organized as:
     // - 0: Input shared memory pool
     // - 1: Output shared memory pool
     // - [2, 2+i): Input device memories
     // - [2+i, 2+i+o): Output device memories
-    DeviceMemoryAllocator allocator(device, preparedModel, testModel);
-    std::vector<sp<IBuffer>> buffers;
+    DeviceMemoryAllocator allocator(kDevice, kPreparedModel, testModel);
     std::vector<uint32_t> tokens;
+    mBuffers.clear();
 
     // Model inputs.
     hidl_vec<RequestArgument> inputs(testModel.main.inputIndexes.size());
@@ -363,13 +377,13 @@
             // Omitted input.
             inputs[i] = {.hasNoValue = true};
             continue;
-        } else if (preferDeviceMemory) {
+        } else if (memoryType == MemoryType::DEVICE) {
             SCOPED_TRACE("Input index = " + std::to_string(i));
             auto [buffer, token] = allocator.allocate<IOType::INPUT>(i);
             if (buffer != nullptr) {
-                DataLocation loc = {.poolIndex = static_cast<uint32_t>(buffers.size() +
+                DataLocation loc = {.poolIndex = static_cast<uint32_t>(mBuffers.size() +
                                                                        kDeviceMemoryBeginIndex)};
-                buffers.push_back(std::move(buffer));
+                mBuffers.push_back(std::move(buffer));
                 tokens.push_back(token);
                 inputs[i] = {.hasNoValue = false, .location = loc, .dimensions = {}};
                 continue;
@@ -389,13 +403,13 @@
     size_t outputSize = 0;
     for (uint32_t i = 0; i < testModel.main.outputIndexes.size(); i++) {
         const auto& op = testModel.main.operands[testModel.main.outputIndexes[i]];
-        if (preferDeviceMemory) {
+        if (memoryType == MemoryType::DEVICE) {
             SCOPED_TRACE("Output index = " + std::to_string(i));
             auto [buffer, token] = allocator.allocate<IOType::OUTPUT>(i);
             if (buffer != nullptr) {
-                DataLocation loc = {.poolIndex = static_cast<uint32_t>(buffers.size() +
+                DataLocation loc = {.poolIndex = static_cast<uint32_t>(mBuffers.size() +
                                                                        kDeviceMemoryBeginIndex)};
-                buffers.push_back(std::move(buffer));
+                mBuffers.push_back(std::move(buffer));
                 tokens.push_back(token);
                 outputs[i] = {.hasNoValue = false, .location = loc, .dimensions = {}};
                 continue;
@@ -418,21 +432,29 @@
         outputs[i] = {.hasNoValue = false, .location = loc, .dimensions = {}};
     }
 
+    if (memoryType == MemoryType::DEVICE && mBuffers.empty()) {
+        return std::nullopt;
+    }
+
     // Memory pools.
-    hidl_vec<Request::MemoryPool> pools(kDeviceMemoryBeginIndex + buffers.size());
-    pools[kInputPoolIndex].hidlMemory(nn::allocateSharedMemory(std::max<size_t>(inputSize, 1)));
-    pools[kOutputPoolIndex].hidlMemory(nn::allocateSharedMemory(std::max<size_t>(outputSize, 1)));
-    CHECK_NE(pools[kInputPoolIndex].hidlMemory().size(), 0u);
-    CHECK_NE(pools[kOutputPoolIndex].hidlMemory().size(), 0u);
-    for (uint32_t i = 0; i < buffers.size(); i++) {
+    hidl_vec<Request::MemoryPool> pools(kDeviceMemoryBeginIndex + mBuffers.size());
+    if (memoryType == MemoryType::BLOB_AHWB) {
+        mInputMemory = TestBlobAHWB::create(std::max<size_t>(inputSize, 1));
+        mOutputMemory = TestBlobAHWB::create(std::max<size_t>(outputSize, 1));
+    } else {
+        mInputMemory = TestAshmem::create(std::max<size_t>(inputSize, 1));
+        mOutputMemory = TestAshmem::create(std::max<size_t>(outputSize, 1));
+    }
+    EXPECT_NE(mInputMemory, nullptr);
+    EXPECT_NE(mOutputMemory, nullptr);
+    pools[kInputPoolIndex].hidlMemory(mInputMemory->getHidlMemory());
+    pools[kOutputPoolIndex].hidlMemory(mOutputMemory->getHidlMemory());
+    for (uint32_t i = 0; i < mBuffers.size(); i++) {
         pools[kDeviceMemoryBeginIndex + i].token(tokens[i]);
     }
 
     // Copy input data to the input shared memory pool.
-    sp<IMemory> inputMemory = mapMemory(pools[kInputPoolIndex].hidlMemory());
-    CHECK(inputMemory.get() != nullptr);
-    uint8_t* inputPtr = static_cast<uint8_t*>(static_cast<void*>(inputMemory->getPointer()));
-    CHECK(inputPtr != nullptr);
+    uint8_t* inputPtr = mInputMemory->getPointer();
     for (uint32_t i = 0; i < testModel.main.inputIndexes.size(); i++) {
         if (!inputs[i].hasNoValue && inputs[i].location.poolIndex == kInputPoolIndex) {
             const auto& op = testModel.main.operands[testModel.main.inputIndexes[i]];
@@ -441,14 +463,38 @@
             std::copy(begin, end, inputPtr + inputs[i].location.offset);
         }
     }
-
-    Request request = {
+    return Request{
             .inputs = std::move(inputs), .outputs = std::move(outputs), .pools = std::move(pools)};
-    return {std::move(request), std::move(buffers)};
+}
+
+std::vector<TestBuffer> ExecutionContextV1_3::getOutputBuffers(const TestModel& testModel,
+                                                               const Request& request) const {
+    // Copy out output results.
+    uint8_t* outputPtr = mOutputMemory->getPointer();
+    std::vector<TestBuffer> outputBuffers;
+    for (uint32_t i = 0; i < request.outputs.size(); i++) {
+        const auto& outputLoc = request.outputs[i].location;
+        if (outputLoc.poolIndex == kOutputPoolIndex) {
+            outputBuffers.emplace_back(outputLoc.length, outputPtr + outputLoc.offset);
+        } else {
+            const auto& op = testModel.main.operands[testModel.main.outputIndexes[i]];
+            if (op.data.size() == 0) {
+                outputBuffers.emplace_back(0, nullptr);
+            } else {
+                SCOPED_TRACE("Output index = " + std::to_string(i));
+                const uint32_t bufferIndex = outputLoc.poolIndex - kDeviceMemoryBeginIndex;
+                TestBuffer buffer;
+                getBuffer(mBuffers[bufferIndex], op.data.size(), &buffer);
+                outputBuffers.push_back(std::move(buffer));
+            }
+        }
+    }
+    return outputBuffers;
 }
 
 // Get a TestBuffer with data copied from an IBuffer object.
-static void getBuffer(const sp<IBuffer>& buffer, size_t size, TestBuffer* testBuffer) {
+void ExecutionContextV1_3::getBuffer(const sp<IBuffer>& buffer, size_t size,
+                                     TestBuffer* testBuffer) const {
     // IBuffer -> Shared memory.
     hidl_memory tmp = nn::allocateSharedMemory(size);
     const auto ret = buffer->copyTo(tmp);
@@ -464,35 +510,6 @@
     *testBuffer = TestBuffer(size, outputPtr);
 }
 
-static std::vector<TestBuffer> getOutputBuffers(const TestModel& testModel, const Request& request,
-                                                const std::vector<sp<IBuffer>>& buffers) {
-    sp<IMemory> outputMemory = mapMemory(request.pools[kOutputPoolIndex].hidlMemory());
-    CHECK(outputMemory.get() != nullptr);
-    uint8_t* outputPtr = static_cast<uint8_t*>(static_cast<void*>(outputMemory->getPointer()));
-    CHECK(outputPtr != nullptr);
-
-    // Copy out output results.
-    std::vector<TestBuffer> outputBuffers;
-    for (uint32_t i = 0; i < request.outputs.size(); i++) {
-        const auto& outputLoc = request.outputs[i].location;
-        if (outputLoc.poolIndex == kOutputPoolIndex) {
-            outputBuffers.emplace_back(outputLoc.length, outputPtr + outputLoc.offset);
-        } else {
-            const auto& op = testModel.main.operands[testModel.main.outputIndexes[i]];
-            if (op.data.size() == 0) {
-                outputBuffers.emplace_back();
-            } else {
-                SCOPED_TRACE("Output index = " + std::to_string(i));
-                const uint32_t bufferIndex = outputLoc.poolIndex - kDeviceMemoryBeginIndex;
-                TestBuffer buffer;
-                getBuffer(buffers[bufferIndex], op.data.size(), &buffer);
-                outputBuffers.push_back(std::move(buffer));
-            }
-        }
-    }
-    return outputBuffers;
-}
-
 static bool hasZeroSizedOutput(const TestModel& testModel) {
     return std::any_of(testModel.main.outputIndexes.begin(), testModel.main.outputIndexes.end(),
                        [&testModel](uint32_t index) {
@@ -543,13 +560,14 @@
         return;
     }
 
-    auto [request, buffers] =
-            createRequest(device, preparedModel, testModel,
-                          /*preferDeviceMemory=*/testConfig.memoryType == MemoryType::DEVICE);
+    ExecutionContextV1_3 context(device, preparedModel);
+    auto maybeRequest = context.createRequest(testModel, testConfig.memoryType);
     // Skip if testing memory domain but no device memory has been allocated.
-    if (testConfig.memoryType == MemoryType::DEVICE && buffers.empty()) {
+    if (!maybeRequest.has_value()) {
         return;
     }
+
+    Request request = std::move(maybeRequest.value());
     if (testConfig.outputType == OutputType::INSUFFICIENT) {
         makeOutputInsufficientSize(/*outputIndex=*/0, &request);
     }
@@ -648,6 +666,7 @@
                 ASSERT_EQ(syncFenceHandle.getNativeHandle(), nullptr);
                 ASSERT_EQ(fencedCallback, nullptr);
                 executionStatus = result;
+                timing = {UINT64_MAX, UINT64_MAX};
             } else if (syncFenceHandle.getNativeHandle()) {
                 // If a sync fence is returned, try start another run waiting for the sync fence.
                 ret = preparedModel->executeFenced(request, {syncFenceHandle},
@@ -744,7 +763,7 @@
     }
 
     // Retrieve execution results.
-    const std::vector<TestBuffer> outputs = getOutputBuffers(testModel, request, buffers);
+    const std::vector<TestBuffer> outputs = context.getOutputBuffers(testModel, request);
 
     // We want "close-enough" results.
     checkResults(testModel, outputs);
@@ -755,29 +774,32 @@
     std::vector<OutputType> outputTypesList;
     std::vector<MeasureTiming> measureTimingList;
     std::vector<Executor> executorList;
-    MemoryType memoryType = MemoryType::SHARED;
+    std::vector<MemoryType> memoryTypeList;
 
     switch (testKind) {
         case TestKind::GENERAL: {
             outputTypesList = {OutputType::FULLY_SPECIFIED};
             measureTimingList = {MeasureTiming::NO, MeasureTiming::YES};
             executorList = {Executor::ASYNC, Executor::SYNC, Executor::BURST};
+            memoryTypeList = {MemoryType::ASHMEM};
         } break;
         case TestKind::DYNAMIC_SHAPE: {
             outputTypesList = {OutputType::UNSPECIFIED, OutputType::INSUFFICIENT};
             measureTimingList = {MeasureTiming::NO, MeasureTiming::YES};
             executorList = {Executor::ASYNC, Executor::SYNC, Executor::BURST, Executor::FENCED};
+            memoryTypeList = {MemoryType::ASHMEM};
         } break;
         case TestKind::MEMORY_DOMAIN: {
             outputTypesList = {OutputType::FULLY_SPECIFIED};
             measureTimingList = {MeasureTiming::NO};
             executorList = {Executor::ASYNC, Executor::SYNC, Executor::FENCED};
-            memoryType = MemoryType::DEVICE;
+            memoryTypeList = {MemoryType::BLOB_AHWB, MemoryType::DEVICE};
         } break;
         case TestKind::FENCED_COMPUTE: {
             outputTypesList = {OutputType::FULLY_SPECIFIED};
             measureTimingList = {MeasureTiming::NO, MeasureTiming::YES};
             executorList = {Executor::FENCED};
+            memoryTypeList = {MemoryType::ASHMEM};
         } break;
         case TestKind::QUANTIZATION_COUPLING: {
             LOG(FATAL) << "Wrong TestKind for EvaluatePreparedModel";
@@ -788,14 +810,17 @@
             measureTimingList = {MeasureTiming::NO, MeasureTiming::YES};
             // Burst does not support V1_3 loop timeout.
             executorList = {Executor::ASYNC, Executor::SYNC, Executor::FENCED};
+            memoryTypeList = {MemoryType::ASHMEM};
         } break;
     }
 
     for (const OutputType outputType : outputTypesList) {
         for (const MeasureTiming measureTiming : measureTimingList) {
             for (const Executor executor : executorList) {
-                const TestConfig testConfig(executor, measureTiming, outputType, memoryType);
-                EvaluatePreparedModel(device, preparedModel, testModel, testConfig);
+                for (const MemoryType memoryType : memoryTypeList) {
+                    const TestConfig testConfig(executor, measureTiming, outputType, memoryType);
+                    EvaluatePreparedModel(device, preparedModel, testModel, testConfig);
+                }
             }
         }
     }
@@ -814,7 +839,7 @@
     for (const OutputType outputType : outputTypesList) {
         for (const MeasureTiming measureTiming : measureTimingList) {
             for (const Executor executor : executorList) {
-                const TestConfig testConfig(executor, measureTiming, outputType, MemoryType::SHARED,
+                const TestConfig testConfig(executor, measureTiming, outputType, MemoryType::ASHMEM,
                                             /*reportSkipping=*/false);
                 bool baseSkipped = false;
                 EvaluatePreparedModel(device, preparedModel, testModel, testConfig, &baseSkipped);
@@ -891,6 +916,10 @@
     return TestModelManager::get().getTestModels(filter);
 }
 
+std::vector<NamedModel> getNamedModels(const FilterNameFn& filter) {
+    return TestModelManager::get().getTestModels(filter);
+}
+
 std::string printGeneratedTest(const testing::TestParamInfo<GeneratedTestParam>& info) {
     const auto& [namedDevice, namedModel] = info.param;
     return gtestCompliantName(getName(namedDevice) + "_" + getName(namedModel));
diff --git a/neuralnetworks/1.3/vts/functional/GeneratedTestHarness.h b/neuralnetworks/1.3/vts/functional/GeneratedTestHarness.h
index 834d335..4f05c48 100644
--- a/neuralnetworks/1.3/vts/functional/GeneratedTestHarness.h
+++ b/neuralnetworks/1.3/vts/functional/GeneratedTestHarness.h
@@ -41,6 +41,9 @@
 using FilterFn = std::function<bool(const test_helper::TestModel&)>;
 std::vector<NamedModel> getNamedModels(const FilterFn& filter);
 
+using FilterNameFn = std::function<bool(const std::string&)>;
+std::vector<NamedModel> getNamedModels(const FilterNameFn& filter);
+
 std::string printGeneratedTest(const testing::TestParamInfo<GeneratedTestParam>& info);
 
 #define INSTANTIATE_GENERATED_TEST(TestSuite, filter)                                     \
@@ -77,6 +80,8 @@
 void EvaluatePreparedModel(const sp<IDevice>& device, const sp<IPreparedModel>& preparedModel,
                            const test_helper::TestModel& testModel, TestKind testKind);
 
+void waitForSyncFence(int syncFd);
+
 }  // namespace android::hardware::neuralnetworks::V1_3::vts::functional
 
 #endif  // ANDROID_HARDWARE_NEURALNETWORKS_V1_3_GENERATED_TEST_HARNESS_H
diff --git a/neuralnetworks/1.3/vts/functional/MemoryDomainTests.cpp b/neuralnetworks/1.3/vts/functional/MemoryDomainTests.cpp
new file mode 100644
index 0000000..3c0c885
--- /dev/null
+++ b/neuralnetworks/1.3/vts/functional/MemoryDomainTests.cpp
@@ -0,0 +1,1203 @@
+/*
+ * Copyright (C) 2020 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.
+ */
+
+#define LOG_TAG "neuralnetworks_hidl_hal_test"
+
+#include <android-base/logging.h>
+#include <gtest/gtest.h>
+
+#include "1.3/Callbacks.h"
+#include "1.3/Utils.h"
+#include "GeneratedTestHarness.h"
+#include "MemoryUtils.h"
+#include "TestHarness.h"
+#include "Utils.h"
+#include "VtsHalNeuralnetworks.h"
+
+namespace android::hardware::neuralnetworks::V1_3::vts::functional {
+
+using namespace test_helper;
+using implementation::ExecutionCallback;
+using implementation::PreparedModelCallback;
+using V1_0::RequestArgument;
+using V1_1::ExecutionPreference;
+using V1_2::Constant;
+using V1_2::MeasureTiming;
+using V1_2::OutputShape;
+using V1_2::Timing;
+
+namespace {
+
+const auto kNamedDeviceChoices = testing::ValuesIn(getNamedDevices());
+
+// A 1.3 driver is likely to support at least one of the following operand types.
+const std::vector<TestOperandType> kTestOperandTypeChoicesVector = {
+        TestOperandType::TENSOR_FLOAT32,
+        TestOperandType::TENSOR_FLOAT16,
+        TestOperandType::TENSOR_QUANT8_ASYMM,
+        TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+};
+const auto kTestOperandTypeChoices = testing::ValuesIn(kTestOperandTypeChoicesVector);
+
+bool isInChoices(TestOperandType type) {
+    return std::count(kTestOperandTypeChoicesVector.begin(), kTestOperandTypeChoicesVector.end(),
+                      type) > 0;
+}
+
+bool isFloat(TestOperandType type) {
+    CHECK(isInChoices(type));
+    return type == TestOperandType::TENSOR_FLOAT32 || type == TestOperandType::TENSOR_FLOAT16;
+}
+
+// Create dummy buffers for model constants as well as inputs and outputs.
+// We only care about the size here because we will not check accuracy in validation tests.
+void createDummyData(TestModel* testModel) {
+    for (auto& operand : testModel->main.operands) {
+        if (operand.data != nullptr) continue;
+        switch (operand.lifetime) {
+            case TestOperandLifeTime::SUBGRAPH_INPUT:
+            case TestOperandLifeTime::SUBGRAPH_OUTPUT:
+            case TestOperandLifeTime::CONSTANT_COPY:
+            case TestOperandLifeTime::CONSTANT_REFERENCE: {
+                const uint32_t size = nn::nonExtensionOperandSizeOfData(
+                        static_cast<OperandType>(operand.type), operand.dimensions);
+                operand.data = TestBuffer(size);
+            } break;
+            default:
+                break;
+        }
+    }
+}
+
+TestOperand createInt32Scalar(int32_t value) {
+    return {
+            .type = TestOperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = TestOperandLifeTime::CONSTANT_COPY,
+            .data = TestBuffer::createFromVector<int32_t>({value}),
+    };
+}
+
+// Construct a test model with multiple CONV_2D operations with the given operand as inputs.
+// The dimensions of the filters are chosen to ensure outputs has the same dimensions as inputs.
+// We choose CONV_2D operation because it is commonly supported by most drivers.
+TestModel createConvModel(const TestOperand& operand, uint32_t numOperations) {
+    CHECK(isInChoices(operand.type));
+
+    TestOperand weight = {.type = operand.type,
+                          .dimensions = {operand.dimensions[3], 3, 3, operand.dimensions[3]},
+                          .numberOfConsumers = 1,
+                          .scale = isFloat(operand.type) ? 0.0f : 1.0f,
+                          .zeroPoint = 0,
+                          .lifetime = TestOperandLifeTime::CONSTANT_COPY};
+
+    TestOperand bias = {
+            .type = isFloat(operand.type) ? operand.type : TestOperandType::TENSOR_INT32,
+            .dimensions = {operand.dimensions[3]},
+            .numberOfConsumers = 1,
+            .scale = operand.scale * weight.scale,
+            .zeroPoint = 0,
+            .lifetime = TestOperandLifeTime::CONSTANT_COPY};
+
+    TestOperand output = operand;
+    output.numberOfConsumers = 0;
+    output.lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT;
+
+    const std::vector<TestOperand> operands = {
+            operand,
+            std::move(weight),
+            std::move(bias),
+            createInt32Scalar(1),  // same padding
+            createInt32Scalar(1),  // width stride
+            createInt32Scalar(1),  // height stride
+            createInt32Scalar(0),  // activation = NONE
+            std::move(output),
+    };
+
+    TestModel model;
+    for (uint32_t i = 0; i < numOperations; i++) {
+        model.main.operands.insert(model.main.operands.end(), operands.begin(), operands.end());
+        const uint32_t inputIndex = operands.size() * i;
+        const uint32_t outputIndex = inputIndex + operands.size() - 1;
+        std::vector<uint32_t> inputs(operands.size() - 1);
+        std::iota(inputs.begin(), inputs.end(), inputIndex);
+        model.main.operations.push_back({.type = TestOperationType::CONV_2D,
+                                         .inputs = std::move(inputs),
+                                         .outputs = {outputIndex}});
+        model.main.inputIndexes.push_back(inputIndex);
+        model.main.outputIndexes.push_back(outputIndex);
+    }
+    createDummyData(&model);
+    return model;
+}
+
+// Construct a test model with a single ADD operation with the given operand as input0 and input1.
+// This is to cover additional cases that the CONV_2D model does not support, e.g. arbitrary input
+// operand rank, scalar input operand. We choose ADD operation because it is commonly supported by
+// most drivers.
+TestModel createSingleAddModel(const TestOperand& operand) {
+    CHECK(isInChoices(operand.type));
+
+    TestOperand act = {
+            .type = TestOperandType::INT32,
+            .dimensions = {},
+            .numberOfConsumers = 1,
+            .scale = 0.0f,
+            .zeroPoint = 0,
+            .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+    };
+
+    TestOperand output = operand;
+    output.numberOfConsumers = 0;
+    output.lifetime = TestOperandLifeTime::SUBGRAPH_OUTPUT;
+
+    TestModel model = {
+            .main =
+                    {
+                            .operands =
+                                    {
+                                            operand,
+                                            operand,
+                                            std::move(act),
+                                            output,
+                                    },
+                            .operations = {{.type = TestOperationType::ADD,
+                                            .inputs = {0, 1, 2},
+                                            .outputs = {3}}},
+                            .inputIndexes = {0, 1, 2},
+                            .outputIndexes = {3},
+                    },
+    };
+    createDummyData(&model);
+    return model;
+}
+
+// A dummy invalid IPreparedModel class for MemoryDomainAllocateTest.InvalidPreparedModel
+class InvalidPreparedModel : public IPreparedModel {
+  public:
+    Return<V1_0::ErrorStatus> execute(const V1_0::Request&,
+                                      const sp<V1_0::IExecutionCallback>&) override {
+        return V1_0::ErrorStatus::GENERAL_FAILURE;
+    }
+    Return<V1_0::ErrorStatus> execute_1_2(const V1_0::Request&, V1_2::MeasureTiming,
+                                          const sp<V1_2::IExecutionCallback>&) override {
+        return V1_0::ErrorStatus::GENERAL_FAILURE;
+    }
+    Return<V1_3::ErrorStatus> execute_1_3(const V1_3::Request&, V1_2::MeasureTiming,
+                                          const V1_3::OptionalTimePoint&,
+                                          const V1_3::OptionalTimeoutDuration&,
+                                          const sp<V1_3::IExecutionCallback>&) override {
+        return V1_3::ErrorStatus::GENERAL_FAILURE;
+    }
+    Return<void> executeSynchronously(const V1_0::Request&, V1_2::MeasureTiming,
+                                      executeSynchronously_cb) override {
+        return Void();
+    }
+    Return<void> executeSynchronously_1_3(const V1_3::Request&, V1_2::MeasureTiming,
+                                          const V1_3::OptionalTimePoint&,
+                                          const V1_3::OptionalTimeoutDuration&,
+                                          executeSynchronously_1_3_cb) override {
+        return Void();
+    }
+    Return<void> configureExecutionBurst(const sp<V1_2::IBurstCallback>&,
+                                         const MQDescriptorSync<V1_2::FmqRequestDatum>&,
+                                         const MQDescriptorSync<V1_2::FmqResultDatum>&,
+                                         configureExecutionBurst_cb) override {
+        return Void();
+    }
+    Return<void> executeFenced(const V1_3::Request&, const hidl_vec<hidl_handle>&,
+                               V1_2::MeasureTiming, const V1_3::OptionalTimePoint&,
+                               const V1_3::OptionalTimeoutDuration&,
+                               const V1_3::OptionalTimeoutDuration&, executeFenced_cb) override {
+        return Void();
+    }
+};
+
+}  // namespace
+
+class MemoryDomainTestBase : public testing::Test {
+  protected:
+    MemoryDomainTestBase(sp<IDevice> device, TestOperandType type)
+        : kDevice(std::move(device)),
+          kTestOperandType(type),
+          kTestOperand(kTestOperandMap.at(type)),
+          kTestOperandDataSize(nn::nonExtensionOperandSizeOfData(static_cast<OperandType>(type),
+                                                                 kTestOperand.dimensions)) {}
+
+    void SetUp() override {
+        testing::Test::SetUp();
+        ASSERT_NE(kDevice, nullptr);
+    }
+
+    sp<IPreparedModel> createConvPreparedModel(const TestOperand& testOperand,
+                                               uint32_t numOperations = 1) {
+        const TestModel testModel = createConvModel(testOperand, numOperations);
+        const Model model = createModel(testModel);
+        sp<IPreparedModel> preparedModel;
+        createPreparedModel(kDevice, model, &preparedModel, /*reportSkipping=*/false);
+        return preparedModel;
+    }
+
+    sp<IPreparedModel> createAddPreparedModel(const TestOperand& testOperand) {
+        const TestModel testModel = createSingleAddModel(testOperand);
+        const Model model = createModel(testModel);
+        sp<IPreparedModel> preparedModel;
+        createPreparedModel(kDevice, model, &preparedModel, /*reportSkipping=*/false);
+        return preparedModel;
+    }
+
+    static const std::map<TestOperandType, TestOperand> kTestOperandMap;
+
+    const sp<IDevice> kDevice;
+    const TestOperandType kTestOperandType;
+    const TestOperand& kTestOperand;
+    const uint32_t kTestOperandDataSize;
+};
+
+const std::map<TestOperandType, TestOperand> MemoryDomainTestBase::kTestOperandMap = {
+        {TestOperandType::TENSOR_FLOAT32,
+         {
+                 .type = TestOperandType::TENSOR_FLOAT32,
+                 .dimensions = {1, 32, 32, 8},
+                 .numberOfConsumers = 1,
+                 .scale = 0.0f,
+                 .zeroPoint = 0,
+                 .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+         }},
+        {TestOperandType::TENSOR_FLOAT16,
+         {
+                 .type = TestOperandType::TENSOR_FLOAT16,
+                 .dimensions = {1, 32, 32, 8},
+                 .numberOfConsumers = 1,
+                 .scale = 0.0f,
+                 .zeroPoint = 0,
+                 .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+         }},
+        {TestOperandType::TENSOR_QUANT8_ASYMM,
+         {
+                 .type = TestOperandType::TENSOR_QUANT8_ASYMM,
+                 .dimensions = {1, 32, 32, 8},
+                 .numberOfConsumers = 1,
+                 .scale = 0.5f,
+                 .zeroPoint = 0,
+                 .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+         }},
+        {TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+         {
+                 .type = TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED,
+                 .dimensions = {1, 32, 32, 8},
+                 .numberOfConsumers = 1,
+                 .scale = 0.5f,
+                 .zeroPoint = 0,
+                 .lifetime = TestOperandLifeTime::SUBGRAPH_INPUT,
+         }},
+};
+
+using MemoryDomainAllocateTestParam = std::tuple<NamedDevice, TestOperandType>;
+class MemoryDomainAllocateTest : public MemoryDomainTestBase,
+                                 public testing::WithParamInterface<MemoryDomainAllocateTestParam> {
+  protected:
+    MemoryDomainAllocateTest()
+        : MemoryDomainTestBase(getData(std::get<NamedDevice>(GetParam())),
+                               std::get<TestOperandType>(GetParam())) {}
+
+    struct AllocateTestArgs {
+        hidl_vec<uint32_t> dimensions;
+        hidl_vec<sp<IPreparedModel>> preparedModels;
+        hidl_vec<BufferRole> inputRoles;
+        hidl_vec<BufferRole> outputRoles;
+    };
+
+    // Validation test for IDevice::allocate. The driver is expected to fail with INVALID_ARGUMENT,
+    // or GENERAL_FAILURE if memory domain is not supported.
+    void validateAllocate(AllocateTestArgs args) {
+        const auto ret = kDevice->allocate(
+                {.dimensions = std::move(args.dimensions)}, std::move(args.preparedModels),
+                std::move(args.inputRoles), std::move(args.outputRoles),
+                [](ErrorStatus status, const sp<IBuffer>& buffer, uint32_t token) {
+                    EXPECT_TRUE(status == ErrorStatus::INVALID_ARGUMENT ||
+                                status == ErrorStatus::GENERAL_FAILURE);
+                    EXPECT_EQ(buffer, nullptr);
+                    EXPECT_EQ(token, 0);
+                });
+        ASSERT_TRUE(ret.isOk());
+    }
+
+    void testConflictOperands(const sp<IPreparedModel>& model1, const sp<IPreparedModel>& model2) {
+        validateAllocate({
+                .preparedModels = {model1, model2},
+                .inputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f},
+                               {.modelIndex = 1, .ioIndex = 0, .frequency = 1.0f}},
+        });
+        validateAllocate({
+                .preparedModels = {model1, model2},
+                .inputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f}},
+                .outputRoles = {{.modelIndex = 1, .ioIndex = 0, .frequency = 1.0f}},
+        });
+        validateAllocate({
+                .preparedModels = {model1, model2},
+                .outputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f},
+                                {.modelIndex = 1, .ioIndex = 0, .frequency = 1.0f}},
+        });
+    }
+};
+
+TEST_P(MemoryDomainAllocateTest, EmptyRole) {
+    // Test with empty prepared models and roles.
+    validateAllocate({});
+
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    if (preparedModel == nullptr) return;
+
+    // Test again with non-empty prepared models but empty roles.
+    validateAllocate({
+            .preparedModels = {preparedModel},
+    });
+}
+
+TEST_P(MemoryDomainAllocateTest, NullptrPreparedModel) {
+    // Test with nullptr prepared model as input role.
+    validateAllocate({
+            .preparedModels = {nullptr},
+            .inputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f}},
+    });
+
+    // Test with nullptr prepared model as output role.
+    validateAllocate({
+            .preparedModels = {nullptr},
+            .outputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f}},
+    });
+}
+
+TEST_P(MemoryDomainAllocateTest, InvalidPreparedModel) {
+    sp<InvalidPreparedModel> invalidPreparedModel = new InvalidPreparedModel();
+
+    // Test with invalid prepared model as input role.
+    validateAllocate({
+            .preparedModels = {invalidPreparedModel},
+            .inputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f}},
+    });
+
+    // Test with invalid prepared model as output role.
+    validateAllocate({
+            .preparedModels = {invalidPreparedModel},
+            .outputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f}},
+    });
+}
+
+TEST_P(MemoryDomainAllocateTest, InvalidModelIndex) {
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    if (preparedModel == nullptr) return;
+
+    // This should fail, because the model index is out of bound.
+    validateAllocate({
+            .preparedModels = {preparedModel},
+            .inputRoles = {{.modelIndex = 1, .ioIndex = 0, .frequency = 1.0f}},
+    });
+
+    // This should fail, because the model index is out of bound.
+    validateAllocate({
+            .preparedModels = {preparedModel},
+            .outputRoles = {{.modelIndex = 1, .ioIndex = 0, .frequency = 1.0f}},
+    });
+}
+
+TEST_P(MemoryDomainAllocateTest, InvalidIOIndex) {
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    if (preparedModel == nullptr) return;
+
+    // This should fail, because the model only has one input.
+    validateAllocate({
+            .preparedModels = {preparedModel},
+            .inputRoles = {{.modelIndex = 0, .ioIndex = 1, .frequency = 1.0f}},
+    });
+
+    // This should fail, because the model only has one output.
+    validateAllocate({
+            .preparedModels = {preparedModel},
+            .outputRoles = {{.modelIndex = 0, .ioIndex = 1, .frequency = 1.0f}},
+    });
+}
+
+TEST_P(MemoryDomainAllocateTest, InvalidFrequency) {
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    if (preparedModel == nullptr) return;
+
+    for (float invalidFreq : {10.0f, 0.0f, -0.5f}) {
+        // Test with invalid frequency for input roles.
+        validateAllocate({
+                .preparedModels = {preparedModel},
+                .inputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = invalidFreq}},
+        });
+        // Test with invalid frequency for output roles.
+        validateAllocate({
+                .preparedModels = {preparedModel},
+                .outputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = invalidFreq}},
+        });
+    }
+}
+
+TEST_P(MemoryDomainAllocateTest, SameRoleSpecifiedTwice) {
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    if (preparedModel == nullptr) return;
+
+    // Same role with same model index.
+    validateAllocate({
+            .preparedModels = {preparedModel},
+            .inputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f},
+                           {.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f}},
+    });
+    validateAllocate({
+            .preparedModels = {preparedModel},
+            .outputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f},
+                            {.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f}},
+    });
+
+    // Different model indexes, but logically referring to the same role.
+    validateAllocate({
+            .preparedModels = {preparedModel, preparedModel},
+            .inputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f},
+                           {.modelIndex = 1, .ioIndex = 0, .frequency = 1.0f}},
+    });
+    validateAllocate({
+            .preparedModels = {preparedModel, preparedModel},
+            .outputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f},
+                            {.modelIndex = 1, .ioIndex = 0, .frequency = 1.0f}},
+    });
+}
+
+TEST_P(MemoryDomainAllocateTest, ConflictOperandType) {
+    const std::map<TestOperandType, TestOperandType> conflictTypeMap = {
+            {TestOperandType::TENSOR_FLOAT32, TestOperandType::TENSOR_FLOAT16},
+            {TestOperandType::TENSOR_FLOAT16, TestOperandType::TENSOR_FLOAT32},
+            {TestOperandType::TENSOR_QUANT8_ASYMM, TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED},
+            {TestOperandType::TENSOR_QUANT8_ASYMM_SIGNED, TestOperandType::TENSOR_QUANT8_ASYMM},
+    };
+
+    TestOperand conflictTestOperand = kTestOperand;
+    const auto it = conflictTypeMap.find(kTestOperandType);
+    ASSERT_FALSE(it == conflictTypeMap.end());
+    conflictTestOperand.type = it->second;
+
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    auto conflictPreparedModel = createConvPreparedModel(conflictTestOperand);
+    if (preparedModel == nullptr || conflictPreparedModel == nullptr) return;
+    testConflictOperands(preparedModel, conflictPreparedModel);
+}
+
+TEST_P(MemoryDomainAllocateTest, ConflictScale) {
+    if (isFloat(kTestOperandType)) return;
+
+    TestOperand conflictTestOperand = kTestOperand;
+    ASSERT_NE(conflictTestOperand.scale, 1.0f);
+    conflictTestOperand.scale = 1.0f;
+
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    auto conflictPreparedModel = createConvPreparedModel(conflictTestOperand);
+    if (preparedModel == nullptr || conflictPreparedModel == nullptr) return;
+    testConflictOperands(preparedModel, conflictPreparedModel);
+}
+
+TEST_P(MemoryDomainAllocateTest, ConflictZeroPoint) {
+    if (isFloat(kTestOperandType)) return;
+
+    TestOperand conflictTestOperand = kTestOperand;
+    ASSERT_NE(conflictTestOperand.zeroPoint, 10);
+    conflictTestOperand.zeroPoint = 10;
+
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    auto conflictPreparedModel = createConvPreparedModel(conflictTestOperand);
+    if (preparedModel == nullptr || conflictPreparedModel == nullptr) return;
+    testConflictOperands(preparedModel, conflictPreparedModel);
+}
+
+TEST_P(MemoryDomainAllocateTest, ConflictRankBetweenRoles) {
+    TestOperand conflictTestOperand = kTestOperand;
+    conflictTestOperand.dimensions.pop_back();
+
+    auto preparedModel = createAddPreparedModel(kTestOperand);
+    auto conflictPreparedModel = createAddPreparedModel(conflictTestOperand);
+    if (preparedModel == nullptr || conflictPreparedModel == nullptr) return;
+    testConflictOperands(preparedModel, conflictPreparedModel);
+}
+
+TEST_P(MemoryDomainAllocateTest, ConflictDimensionsBetweenRoles) {
+    TestOperand conflictTestOperand = kTestOperand;
+    conflictTestOperand.dimensions[0] = 4;
+
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    auto conflictPreparedModel = createConvPreparedModel(conflictTestOperand);
+    if (preparedModel == nullptr || conflictPreparedModel == nullptr) return;
+    testConflictOperands(preparedModel, conflictPreparedModel);
+}
+
+TEST_P(MemoryDomainAllocateTest, ConflictRankBetweenRoleAndDesc) {
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    if (preparedModel == nullptr) return;
+
+    auto badDimensions = kTestOperand.dimensions;
+    badDimensions.pop_back();
+
+    validateAllocate({
+            .dimensions = badDimensions,
+            .preparedModels = {preparedModel},
+            .inputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f}},
+    });
+    validateAllocate({
+            .dimensions = badDimensions,
+            .preparedModels = {preparedModel},
+            .outputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f}},
+    });
+}
+
+TEST_P(MemoryDomainAllocateTest, ConflictDimensionsBetweenRoleAndDesc) {
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    if (preparedModel == nullptr) return;
+
+    auto badDimensions = kTestOperand.dimensions;
+    badDimensions[0] = 4;
+
+    validateAllocate({
+            .dimensions = badDimensions,
+            .preparedModels = {preparedModel},
+            .inputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f}},
+    });
+    validateAllocate({
+            .dimensions = badDimensions,
+            .preparedModels = {preparedModel},
+            .outputRoles = {{.modelIndex = 0, .ioIndex = 0, .frequency = 1.0f}},
+    });
+}
+
+TEST_P(MemoryDomainAllocateTest, ConflictRankWithScalarRole) {
+    auto preparedModel = createAddPreparedModel(kTestOperand);
+    if (preparedModel == nullptr) return;
+
+    // This should fail, because the target operand is a scalar but a non-empty dimension is
+    // specified.
+    validateAllocate({
+            .dimensions = {1},
+            .preparedModels = {preparedModel},
+            .inputRoles = {{.modelIndex = 0, .ioIndex = 2, .frequency = 1.0f}},
+    });
+}
+
+std::string printMemoryDomainAllocateTest(
+        const testing::TestParamInfo<MemoryDomainAllocateTestParam>& info) {
+    const auto& [namedDevice, operandType] = info.param;
+    const std::string type = toString(static_cast<OperandType>(operandType));
+    return gtestCompliantName(getName(namedDevice) + "_" + type);
+}
+
+INSTANTIATE_TEST_CASE_P(TestMemoryDomain, MemoryDomainAllocateTest,
+                        testing::Combine(kNamedDeviceChoices, kTestOperandTypeChoices),
+                        printMemoryDomainAllocateTest);
+
+class MemoryDomainCopyTestBase : public MemoryDomainTestBase {
+  protected:
+    MemoryDomainCopyTestBase(sp<IDevice> device, TestOperandType type)
+        : MemoryDomainTestBase(std::move(device), type) {}
+
+    // Allocates device memory for roles of a single prepared model.
+    // Returns {IBuffer, token} if success; returns {nullptr, 0} if not supported.
+    std::pair<sp<IBuffer>, uint32_t> allocateBuffer(const sp<IPreparedModel>& preparedModel,
+                                                    const std::vector<uint32_t>& inputIndexes,
+                                                    const std::vector<uint32_t>& outputIndexes,
+                                                    const std::vector<uint32_t>& dimensions) {
+        if (preparedModel == nullptr) {
+            return {nullptr, 0};
+        }
+
+        hidl_vec<BufferRole> inputRoles(inputIndexes.size()), outputRoles(outputIndexes.size());
+        auto trans = [](uint32_t ind) -> BufferRole {
+            return {.modelIndex = 0, .ioIndex = ind, .frequency = 1.0f};
+        };
+        std::transform(inputIndexes.begin(), inputIndexes.end(), inputRoles.begin(), trans);
+        std::transform(outputIndexes.begin(), outputIndexes.end(), outputRoles.begin(), trans);
+
+        sp<IBuffer> buffer;
+        uint32_t token = 0;
+        const auto ret = kDevice->allocate(
+                {.dimensions = dimensions}, {preparedModel}, std::move(inputRoles),
+                std::move(outputRoles),
+                [&buffer, &token](ErrorStatus err, const sp<IBuffer>& buf, uint32_t tok) {
+                    if (err == ErrorStatus::NONE) {
+                        EXPECT_NE(buf, nullptr);
+                        EXPECT_GT(tok, 0);
+                        buffer = buf;
+                        token = tok;
+                    } else {
+                        EXPECT_EQ(err, ErrorStatus::GENERAL_FAILURE);
+                        EXPECT_EQ(buf, nullptr);
+                        EXPECT_EQ(tok, 0);
+                    }
+                });
+        EXPECT_TRUE(ret.isOk());
+        return {std::move(buffer), token};
+    }
+
+    std::pair<sp<IBuffer>, uint32_t> allocateBuffer(const sp<IPreparedModel>& preparedModel,
+                                                    const std::vector<uint32_t>& inputIndexes,
+                                                    const std::vector<uint32_t>& outputIndexes) {
+        return allocateBuffer(preparedModel, inputIndexes, outputIndexes, {});
+    }
+
+    hidl_memory allocateSharedMemory(uint32_t size) {
+        hidl_memory memory = nn::allocateSharedMemory(size);
+        EXPECT_EQ(memory.size(), size);
+        return memory;
+    }
+
+    void testCopyFrom(const sp<IBuffer>& buffer, const hidl_memory& memory,
+                      const std::vector<uint32_t>& dimensions, ErrorStatus expectedStatus) {
+        const auto ret = buffer->copyFrom(memory, dimensions);
+        ASSERT_TRUE(ret.isOk());
+        ASSERT_EQ(static_cast<ErrorStatus>(ret), expectedStatus);
+    }
+
+    void testCopyTo(const sp<IBuffer>& buffer, const hidl_memory& memory,
+                    ErrorStatus expectedStatus) {
+        const auto ret = buffer->copyTo(memory);
+        ASSERT_TRUE(ret.isOk());
+        ASSERT_EQ(static_cast<ErrorStatus>(ret), expectedStatus);
+    }
+
+    void initializeDeviceMemory(const sp<IBuffer>& buffer) {
+        hidl_memory memory = nn::allocateSharedMemory(kTestOperandDataSize);
+        ASSERT_EQ(memory.size(), kTestOperandDataSize);
+        testCopyFrom(buffer, memory, kTestOperand.dimensions, ErrorStatus::NONE);
+    }
+};
+
+using MemoryDomainCopyTestParam = std::tuple<NamedDevice, TestOperandType>;
+class MemoryDomainCopyTest : public MemoryDomainCopyTestBase,
+                             public testing::WithParamInterface<MemoryDomainCopyTestParam> {
+  protected:
+    MemoryDomainCopyTest()
+        : MemoryDomainCopyTestBase(getData(std::get<NamedDevice>(GetParam())),
+                                   std::get<TestOperandType>(GetParam())) {}
+};
+
+TEST_P(MemoryDomainCopyTest, CopyFrom_InvalidMemorySize) {
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    auto [buffer, token] = allocateBuffer(preparedModel, {0}, {0});
+    if (buffer == nullptr) return;
+
+    uint32_t badMemorySize1 = kTestOperandDataSize / 2, badMemorySize2 = kTestOperandDataSize * 2;
+    hidl_memory badMemory1 = allocateSharedMemory(badMemorySize1);
+    hidl_memory badMemory2 = allocateSharedMemory(badMemorySize2);
+    testCopyFrom(buffer, badMemory1, {}, ErrorStatus::INVALID_ARGUMENT);
+    testCopyFrom(buffer, badMemory2, {}, ErrorStatus::INVALID_ARGUMENT);
+}
+
+TEST_P(MemoryDomainCopyTest, CopyFrom_InvalidMemorySize_DynamicShape) {
+    TestOperand testOperand = kTestOperand;
+    testOperand.dimensions[0] = 0;
+    auto preparedModel = createConvPreparedModel(testOperand);
+    auto [buffer, token] = allocateBuffer(preparedModel, {0}, {0});
+    if (buffer == nullptr) return;
+
+    uint32_t badMemorySize1 = kTestOperandDataSize / 2, badMemorySize2 = kTestOperandDataSize * 2;
+    hidl_memory badMemory1 = allocateSharedMemory(badMemorySize1);
+    hidl_memory badMemory2 = allocateSharedMemory(badMemorySize2);
+    hidl_memory goodMemory = allocateSharedMemory(kTestOperandDataSize);
+
+    auto badDimensions = kTestOperand.dimensions;
+    badDimensions[0] = 2;
+
+    testCopyFrom(buffer, badMemory1, kTestOperand.dimensions, ErrorStatus::INVALID_ARGUMENT);
+    testCopyFrom(buffer, badMemory2, kTestOperand.dimensions, ErrorStatus::INVALID_ARGUMENT);
+    testCopyFrom(buffer, goodMemory, kTestOperand.dimensions, ErrorStatus::NONE);
+    testCopyFrom(buffer, goodMemory, badDimensions, ErrorStatus::INVALID_ARGUMENT);
+}
+
+TEST_P(MemoryDomainCopyTest, CopyFrom_InvalidDimensions) {
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    auto [buffer, token] = allocateBuffer(preparedModel, {0}, {0});
+    if (buffer == nullptr) return;
+
+    hidl_memory memory = allocateSharedMemory(kTestOperandDataSize);
+
+    std::vector<uint32_t> badDimensions;
+    badDimensions = kTestOperand.dimensions;
+    badDimensions.pop_back();
+    testCopyFrom(buffer, memory, badDimensions, ErrorStatus::INVALID_ARGUMENT);
+
+    badDimensions = kTestOperand.dimensions;
+    badDimensions[0] = 2;
+    testCopyFrom(buffer, memory, badDimensions, ErrorStatus::INVALID_ARGUMENT);
+
+    badDimensions = kTestOperand.dimensions;
+    badDimensions[0] = 0;
+    testCopyFrom(buffer, memory, badDimensions, ErrorStatus::INVALID_ARGUMENT);
+
+    testCopyFrom(buffer, memory, {}, ErrorStatus::NONE);
+    testCopyFrom(buffer, memory, kTestOperand.dimensions, ErrorStatus::NONE);
+}
+
+TEST_P(MemoryDomainCopyTest, CopyFrom_InvalidDimensions_DynamicShape) {
+    TestOperand testOperand = kTestOperand;
+    testOperand.dimensions[0] = 0;
+    auto preparedModel = createConvPreparedModel(testOperand);
+    auto [buffer, token] = allocateBuffer(preparedModel, {0}, {0});
+    if (buffer == nullptr) return;
+
+    hidl_memory memory = allocateSharedMemory(kTestOperandDataSize);
+
+    std::vector<uint32_t> badDimensions;
+    badDimensions = kTestOperand.dimensions;
+    badDimensions.pop_back();
+    testCopyFrom(buffer, memory, badDimensions, ErrorStatus::INVALID_ARGUMENT);
+
+    badDimensions = kTestOperand.dimensions;
+    badDimensions[0] = 2;
+    badDimensions[3] = 4;
+    testCopyFrom(buffer, memory, badDimensions, ErrorStatus::INVALID_ARGUMENT);
+
+    badDimensions = kTestOperand.dimensions;
+    badDimensions[0] = 1;
+    badDimensions[3] = 0;
+    testCopyFrom(buffer, memory, badDimensions, ErrorStatus::INVALID_ARGUMENT);
+
+    testCopyFrom(buffer, memory, {}, ErrorStatus::INVALID_ARGUMENT);
+    testCopyFrom(buffer, memory, kTestOperand.dimensions, ErrorStatus::NONE);
+}
+
+TEST_P(MemoryDomainCopyTest, CopyTo_UninitializedMemory) {
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    auto [buffer, token] = allocateBuffer(preparedModel, {0}, {0});
+    if (buffer == nullptr) return;
+
+    hidl_memory memory = allocateSharedMemory(kTestOperandDataSize);
+    testCopyTo(buffer, memory, ErrorStatus::GENERAL_FAILURE);
+}
+
+TEST_P(MemoryDomainCopyTest, CopyTo_InvalidMemorySize) {
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    auto [buffer, token] = allocateBuffer(preparedModel, {0}, {0});
+    if (buffer == nullptr) return;
+
+    uint32_t badMemorySize1 = kTestOperandDataSize / 2, badMemorySize2 = kTestOperandDataSize * 2;
+    hidl_memory badMemory1 = allocateSharedMemory(badMemorySize1);
+    hidl_memory badMemory2 = allocateSharedMemory(badMemorySize2);
+    hidl_memory goodMemory = allocateSharedMemory(kTestOperandDataSize);
+
+    initializeDeviceMemory(buffer);
+    testCopyTo(buffer, badMemory1, ErrorStatus::INVALID_ARGUMENT);
+    testCopyTo(buffer, badMemory2, ErrorStatus::INVALID_ARGUMENT);
+    testCopyTo(buffer, goodMemory, ErrorStatus::NONE);
+}
+
+TEST_P(MemoryDomainCopyTest, CopyTo_InvalidMemorySize_DynamicShape) {
+    TestOperand testOperand = kTestOperand;
+    testOperand.dimensions[0] = 0;
+    auto preparedModel = createConvPreparedModel(testOperand);
+    auto [buffer, token] = allocateBuffer(preparedModel, {0}, {0});
+    if (buffer == nullptr) return;
+
+    uint32_t badMemorySize1 = kTestOperandDataSize / 2, badMemorySize2 = kTestOperandDataSize * 2;
+    hidl_memory badMemory1 = allocateSharedMemory(badMemorySize1);
+    hidl_memory badMemory2 = allocateSharedMemory(badMemorySize2);
+    hidl_memory goodMemory = allocateSharedMemory(kTestOperandDataSize);
+
+    initializeDeviceMemory(buffer);
+    testCopyTo(buffer, badMemory1, ErrorStatus::INVALID_ARGUMENT);
+    testCopyTo(buffer, badMemory2, ErrorStatus::INVALID_ARGUMENT);
+    testCopyTo(buffer, goodMemory, ErrorStatus::NONE);
+}
+
+std::string printMemoryDomainCopyTest(
+        const testing::TestParamInfo<MemoryDomainCopyTestParam>& info) {
+    const auto& [namedDevice, operandType] = info.param;
+    const std::string type = toString(static_cast<OperandType>(operandType));
+    return gtestCompliantName(getName(namedDevice) + "_" + type);
+}
+
+INSTANTIATE_TEST_CASE_P(TestMemoryDomain, MemoryDomainCopyTest,
+                        testing::Combine(kNamedDeviceChoices, kTestOperandTypeChoices),
+                        printMemoryDomainCopyTest);
+
+using MemoryDomainExecutionTestParam = std::tuple<NamedDevice, TestOperandType, Executor>;
+class MemoryDomainExecutionTest
+    : public MemoryDomainCopyTestBase,
+      public testing::WithParamInterface<MemoryDomainExecutionTestParam> {
+  protected:
+    MemoryDomainExecutionTest()
+        : MemoryDomainCopyTestBase(getData(std::get<NamedDevice>(GetParam())),
+                                   std::get<TestOperandType>(GetParam())) {}
+
+    Request::MemoryPool createSharedMemoryPool(uint32_t size) {
+        hidl_memory memory = allocateSharedMemory(size);
+        Request::MemoryPool pool;
+        pool.hidlMemory(memory);
+        return pool;
+    }
+
+    Request::MemoryPool createDeviceMemoryPool(uint32_t token) {
+        Request::MemoryPool pool;
+        pool.token(token);
+        return pool;
+    }
+
+    void testExecution(const sp<IPreparedModel>& preparedModel, const Request& request,
+                       ErrorStatus expectedStatus) {
+        switch (kExecutor) {
+            case Executor::ASYNC:
+                EXPECT_EQ(executeAsync(preparedModel, request), expectedStatus);
+                break;
+            case Executor::SYNC:
+                EXPECT_EQ(executeSync(preparedModel, request), expectedStatus);
+                break;
+            case Executor::FENCED:
+                EXPECT_EQ(executeFenced(preparedModel, request), expectedStatus);
+                break;
+            default:
+                ASSERT_TRUE(false);
+        }
+    }
+
+    ErrorStatus executeAsync(const sp<IPreparedModel>& preparedModel, const Request& request) {
+        ErrorStatus executionStatus;
+
+        // launch execution
+        sp<ExecutionCallback> executionCallback = new ExecutionCallback();
+        const auto ret =
+                preparedModel->execute_1_3(request, MeasureTiming::NO, {}, {}, executionCallback);
+        EXPECT_TRUE(ret.isOk());
+        executionStatus = static_cast<ErrorStatus>(ret);
+
+        // retrieve execution status
+        executionCallback->wait();
+        if (executionStatus == ErrorStatus::NONE) {
+            executionStatus = executionCallback->getStatus();
+        } else {
+            EXPECT_EQ(executionStatus, executionCallback->getStatus());
+        }
+        const auto timing = executionCallback->getTiming();
+        EXPECT_EQ(UINT64_MAX, timing.timeOnDevice);
+        EXPECT_EQ(UINT64_MAX, timing.timeInDriver);
+        if (executionStatus != ErrorStatus::NONE) {
+            EXPECT_EQ(executionCallback->getOutputShapes().size(), 0);
+        }
+        return executionStatus;
+    }
+
+    ErrorStatus executeSync(const sp<IPreparedModel>& preparedModel, const Request& request) {
+        ErrorStatus executionStatus;
+        const auto ret = preparedModel->executeSynchronously_1_3(
+                request, MeasureTiming::NO, {}, {},
+                [&executionStatus](ErrorStatus error, const hidl_vec<OutputShape>& shapes,
+                                   const Timing& time) {
+                    executionStatus = error;
+                    EXPECT_EQ(UINT64_MAX, time.timeOnDevice);
+                    EXPECT_EQ(UINT64_MAX, time.timeInDriver);
+                    if (executionStatus != ErrorStatus::NONE) {
+                        EXPECT_EQ(shapes.size(), 0);
+                    }
+                });
+        EXPECT_TRUE(ret.isOk());
+        return executionStatus;
+    }
+
+    ErrorStatus executeFenced(const sp<IPreparedModel>& preparedModel, const Request& request) {
+        ErrorStatus executionStatus;
+        hidl_handle syncFenceHandle;
+        sp<IFencedExecutionCallback> fencedCallback;
+        const auto callbackFunc = [&executionStatus, &syncFenceHandle, &fencedCallback](
+                                          ErrorStatus error, const hidl_handle& handle,
+                                          const sp<IFencedExecutionCallback>& callback) {
+            executionStatus = error;
+            syncFenceHandle = handle;
+            fencedCallback = callback;
+        };
+        Return<void> ret = preparedModel->executeFenced(request, {}, MeasureTiming::NO, {}, {}, {},
+                                                        callbackFunc);
+        EXPECT_TRUE(ret.isOk());
+        if (executionStatus != ErrorStatus::NONE) {
+            EXPECT_EQ(syncFenceHandle.getNativeHandle(), nullptr);
+            EXPECT_EQ(fencedCallback, nullptr);
+            return executionStatus;
+        }
+        if (syncFenceHandle.getNativeHandle()) {
+            waitForSyncFence(syncFenceHandle.getNativeHandle()->data[0]);
+        }
+        EXPECT_NE(fencedCallback, nullptr);
+        ret = fencedCallback->getExecutionInfo(
+                [&executionStatus](ErrorStatus error, Timing t, Timing) {
+                    executionStatus = error;
+                    EXPECT_EQ(UINT64_MAX, t.timeOnDevice);
+                    EXPECT_EQ(UINT64_MAX, t.timeInDriver);
+                });
+        EXPECT_TRUE(ret.isOk());
+        return executionStatus;
+    }
+
+    const Executor kExecutor = std::get<Executor>(GetParam());
+};
+
+TEST_P(MemoryDomainExecutionTest, InvalidToken) {
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    if (preparedModel == nullptr) return;
+
+    Request::MemoryPool sharedMemory = createSharedMemoryPool(kTestOperandDataSize);
+    Request::MemoryPool badDeviceMemory1 = createDeviceMemoryPool(0);    // Invalid token.
+    Request::MemoryPool badDeviceMemory2 = createDeviceMemoryPool(100);  // Unknown token.
+    RequestArgument sharedMemoryArg = {
+            .location = {.poolIndex = 0, .offset = 0, .length = kTestOperandDataSize}};
+    RequestArgument deviceMemoryArg = {.location = {.poolIndex = 1}};
+
+    testExecution(preparedModel,
+                  {.inputs = {deviceMemoryArg},
+                   .outputs = {sharedMemoryArg},
+                   .pools = {sharedMemory, badDeviceMemory1}},
+                  ErrorStatus::INVALID_ARGUMENT);
+    testExecution(preparedModel,
+                  {.inputs = {deviceMemoryArg},
+                   .outputs = {sharedMemoryArg},
+                   .pools = {sharedMemory, badDeviceMemory2}},
+                  ErrorStatus::INVALID_ARGUMENT);
+    testExecution(preparedModel,
+                  {.inputs = {sharedMemoryArg},
+                   .outputs = {deviceMemoryArg},
+                   .pools = {sharedMemory, badDeviceMemory1}},
+                  ErrorStatus::INVALID_ARGUMENT);
+    testExecution(preparedModel,
+                  {.inputs = {sharedMemoryArg},
+                   .outputs = {deviceMemoryArg},
+                   .pools = {sharedMemory, badDeviceMemory2}},
+                  ErrorStatus::INVALID_ARGUMENT);
+}
+
+TEST_P(MemoryDomainExecutionTest, InvalidPreparedModel) {
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    auto [buffer, token] = allocateBuffer(preparedModel, {0}, {0});
+    if (buffer == nullptr) return;
+    auto badPreparedModel = createConvPreparedModel(kTestOperand);
+    if (badPreparedModel == nullptr) return;
+
+    Request::MemoryPool sharedMemory = createSharedMemoryPool(kTestOperandDataSize);
+    Request::MemoryPool deviceMemory = createDeviceMemoryPool(token);
+    RequestArgument sharedMemoryArg = {
+            .location = {.poolIndex = 0, .offset = 0, .length = kTestOperandDataSize}};
+    RequestArgument deviceMemoryArg = {.location = {.poolIndex = 1}};
+
+    // This should fail, because the buffer is not allocated for badPreparedModel.
+    initializeDeviceMemory(buffer);
+    testExecution(badPreparedModel,
+                  {.inputs = {deviceMemoryArg},
+                   .outputs = {sharedMemoryArg},
+                   .pools = {sharedMemory, deviceMemory}},
+                  ErrorStatus::INVALID_ARGUMENT);
+    testExecution(badPreparedModel,
+                  {.inputs = {sharedMemoryArg},
+                   .outputs = {deviceMemoryArg},
+                   .pools = {sharedMemory, deviceMemory}},
+                  ErrorStatus::INVALID_ARGUMENT);
+}
+
+TEST_P(MemoryDomainExecutionTest, InvalidIOIndex) {
+    auto preparedModel = createConvPreparedModel(kTestOperand, 2);
+    auto [buffer, token] = allocateBuffer(preparedModel, {0}, {});
+    if (buffer == nullptr) return;
+
+    Request::MemoryPool sharedMemory1 = createSharedMemoryPool(kTestOperandDataSize);
+    Request::MemoryPool sharedMemory2 = createSharedMemoryPool(kTestOperandDataSize);
+    Request::MemoryPool sharedMemory3 = createSharedMemoryPool(kTestOperandDataSize);
+    Request::MemoryPool deviceMemory = createDeviceMemoryPool(token);
+    RequestArgument sharedMemoryArg1 = {
+            .location = {.poolIndex = 0, .offset = 0, .length = kTestOperandDataSize}};
+    RequestArgument sharedMemoryArg2 = {
+            .location = {.poolIndex = 1, .offset = 0, .length = kTestOperandDataSize}};
+    RequestArgument sharedMemoryArg3 = {
+            .location = {.poolIndex = 2, .offset = 0, .length = kTestOperandDataSize}};
+    RequestArgument deviceMemoryArg = {.location = {.poolIndex = 3}};
+
+    // This should fail, because the device memory is not allocated for input 1.
+    initializeDeviceMemory(buffer);
+    testExecution(preparedModel,
+                  {.inputs = {sharedMemoryArg1, deviceMemoryArg},
+                   .outputs = {sharedMemoryArg2, sharedMemoryArg3},
+                   .pools = {sharedMemory1, sharedMemory2, sharedMemory3, deviceMemory}},
+                  ErrorStatus::INVALID_ARGUMENT);
+
+    // This should fail, because the device memory is not allocated for output 1.
+    testExecution(preparedModel,
+                  {.inputs = {sharedMemoryArg1, sharedMemoryArg2},
+                   .outputs = {sharedMemoryArg3, deviceMemoryArg},
+                   .pools = {sharedMemory1, sharedMemory2, sharedMemory3, deviceMemory}},
+                  ErrorStatus::INVALID_ARGUMENT);
+}
+
+TEST_P(MemoryDomainExecutionTest, InvalidIOType) {
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    auto [inputBuffer, inputToken] = allocateBuffer(preparedModel, {0}, {});
+    auto [outputBuffer, outputToken] = allocateBuffer(preparedModel, {}, {0});
+    if (inputBuffer == nullptr || outputBuffer == nullptr) return;
+
+    Request::MemoryPool sharedMemory = createSharedMemoryPool(kTestOperandDataSize);
+    Request::MemoryPool deviceMemory = createDeviceMemoryPool(inputToken);
+    RequestArgument sharedMemoryArg = {
+            .location = {.poolIndex = 0, .offset = 0, .length = kTestOperandDataSize}};
+    RequestArgument deviceMemoryArg = {.location = {.poolIndex = 1}};
+
+    // This should fail, because the device memory is allocated for input but used as output.
+    testExecution(preparedModel,
+                  {.inputs = {sharedMemoryArg},
+                   .outputs = {deviceMemoryArg},
+                   .pools = {sharedMemory, deviceMemory}},
+                  ErrorStatus::INVALID_ARGUMENT);
+
+    // This should fail, because the device memory is allocated for output but used as input.
+    deviceMemory.token(outputToken);
+    initializeDeviceMemory(outputBuffer);
+    testExecution(preparedModel,
+                  {.inputs = {deviceMemoryArg},
+                   .outputs = {sharedMemoryArg},
+                   .pools = {sharedMemory, deviceMemory}},
+                  ErrorStatus::INVALID_ARGUMENT);
+}
+
+TEST_P(MemoryDomainExecutionTest, UninitializedMemory) {
+    auto preparedModel = createConvPreparedModel(kTestOperand);
+    auto [buffer, token] = allocateBuffer(preparedModel, {0}, {0});
+    if (buffer == nullptr) return;
+
+    Request::MemoryPool sharedMemory = createSharedMemoryPool(kTestOperandDataSize);
+    Request::MemoryPool deviceMemory = createDeviceMemoryPool(token);
+    RequestArgument sharedMemoryArg = {
+            .location = {.poolIndex = 0, .offset = 0, .length = kTestOperandDataSize}};
+    RequestArgument deviceMemoryArg = {.location = {.poolIndex = 1}};
+
+    // This should fail, because the device memory is not initialized.
+    testExecution(preparedModel,
+                  {.inputs = {deviceMemoryArg},
+                   .outputs = {sharedMemoryArg},
+                   .pools = {sharedMemory, deviceMemory}},
+                  ErrorStatus::GENERAL_FAILURE);
+
+    // This should initialize the device memory.
+    testExecution(preparedModel,
+                  {.inputs = {sharedMemoryArg},
+                   .outputs = {deviceMemoryArg},
+                   .pools = {sharedMemory, deviceMemory}},
+                  ErrorStatus::NONE);
+
+    // Test again with initialized device memory.
+    testExecution(preparedModel,
+                  {.inputs = {deviceMemoryArg},
+                   .outputs = {sharedMemoryArg},
+                   .pools = {sharedMemory, deviceMemory}},
+                  ErrorStatus::NONE);
+}
+
+TEST_P(MemoryDomainExecutionTest, SameRequestMultipleRoles) {
+    auto preparedModel = createConvPreparedModel(kTestOperand, 2);
+    auto [buffer, token] = allocateBuffer(preparedModel, {0, 1}, {0, 1});
+    if (buffer == nullptr) return;
+
+    Request::MemoryPool sharedMemory1 = createSharedMemoryPool(kTestOperandDataSize);
+    Request::MemoryPool sharedMemory2 = createSharedMemoryPool(kTestOperandDataSize);
+    Request::MemoryPool deviceMemory = createDeviceMemoryPool(token);
+    RequestArgument sharedMemoryArg1 = {
+            .location = {.poolIndex = 0, .offset = 0, .length = kTestOperandDataSize}};
+    RequestArgument sharedMemoryArg2 = {
+            .location = {.poolIndex = 1, .offset = 0, .length = kTestOperandDataSize}};
+    RequestArgument deviceMemoryArg = {.location = {.poolIndex = 2}};
+
+    // This should fail, because the same device memory cannot be used for both input and output.
+    initializeDeviceMemory(buffer);
+    testExecution(preparedModel,
+                  {.inputs = {deviceMemoryArg, sharedMemoryArg1},
+                   .outputs = {deviceMemoryArg, sharedMemoryArg2},
+                   .pools = {sharedMemory1, sharedMemory2, deviceMemory}},
+                  ErrorStatus::INVALID_ARGUMENT);
+
+    // This should fail, because the same device memory cannot be used for multiple outputs.
+    testExecution(preparedModel,
+                  {.inputs = {sharedMemoryArg1, sharedMemoryArg2},
+                   .outputs = {deviceMemoryArg, deviceMemoryArg},
+                   .pools = {sharedMemory1, sharedMemory2, deviceMemory}},
+                  ErrorStatus::INVALID_ARGUMENT);
+
+    // The same device memory can be used for multiple inputs.
+    initializeDeviceMemory(buffer);
+    testExecution(preparedModel,
+                  {.inputs = {deviceMemoryArg, deviceMemoryArg},
+                   .outputs = {sharedMemoryArg1, sharedMemoryArg2},
+                   .pools = {sharedMemory1, sharedMemory2, deviceMemory}},
+                  ErrorStatus::NONE);
+}
+
+TEST_P(MemoryDomainExecutionTest, InvalidDimensions) {
+    // FENCED execution does not support dynamic shape.
+    if (kExecutor == Executor::FENCED) return;
+
+    TestOperand testOperand = kTestOperand;
+    testOperand.dimensions[0] = 0;
+    auto preparedModel = createConvPreparedModel(testOperand);
+    auto [buffer, token] = allocateBuffer(preparedModel, {0}, {0}, kTestOperand.dimensions);
+    if (buffer == nullptr) return;
+
+    Request::MemoryPool sharedMemory = createSharedMemoryPool(kTestOperandDataSize);
+    Request::MemoryPool deviceMemory = createDeviceMemoryPool(token);
+    auto badDimensions = kTestOperand.dimensions;
+    badDimensions[0] = 2;
+    RequestArgument sharedMemoryArg = {
+            .location = {.poolIndex = 0, .offset = 0, .length = kTestOperandDataSize},
+            .dimensions = badDimensions};
+    RequestArgument deviceMemoryArg = {.location = {.poolIndex = 1}};
+    RequestArgument deviceMemoryArgWithBadDimensions = {.location = {.poolIndex = 1},
+                                                        .dimensions = badDimensions};
+
+    initializeDeviceMemory(buffer);
+    testExecution(preparedModel,
+                  {.inputs = {deviceMemoryArgWithBadDimensions},
+                   .outputs = {sharedMemoryArg},
+                   .pools = {sharedMemory, deviceMemory}},
+                  ErrorStatus::INVALID_ARGUMENT);
+
+    testExecution(preparedModel,
+                  {.inputs = {sharedMemoryArg},
+                   .outputs = {deviceMemoryArgWithBadDimensions},
+                   .pools = {sharedMemory, deviceMemory}},
+                  ErrorStatus::INVALID_ARGUMENT);
+
+    testExecution(preparedModel,
+                  {.inputs = {sharedMemoryArg},
+                   .outputs = {deviceMemoryArg},
+                   .pools = {sharedMemory, deviceMemory}},
+                  ErrorStatus::GENERAL_FAILURE);
+}
+
+const auto kExecutorChoices = testing::Values(Executor::ASYNC, Executor::SYNC, Executor::FENCED);
+
+std::string printMemoryDomainExecutionTest(
+        const testing::TestParamInfo<MemoryDomainExecutionTestParam>& info) {
+    const auto& [namedDevice, operandType, executor] = info.param;
+    const std::string type = toString(static_cast<OperandType>(operandType));
+    const std::string executorStr = toString(executor);
+    return gtestCompliantName(getName(namedDevice) + "_" + type + "_" + executorStr);
+}
+
+INSTANTIATE_TEST_CASE_P(TestMemoryDomain, MemoryDomainExecutionTest,
+                        testing::Combine(kNamedDeviceChoices, kTestOperandTypeChoices,
+                                         kExecutorChoices),
+                        printMemoryDomainExecutionTest);
+
+}  // namespace android::hardware::neuralnetworks::V1_3::vts::functional
diff --git a/neuralnetworks/1.3/vts/functional/QualityOfServiceTests.cpp b/neuralnetworks/1.3/vts/functional/QualityOfServiceTests.cpp
index 879989e..2ef1e8f 100644
--- a/neuralnetworks/1.3/vts/functional/QualityOfServiceTests.cpp
+++ b/neuralnetworks/1.3/vts/functional/QualityOfServiceTests.cpp
@@ -214,7 +214,8 @@
 }
 
 void runExecutionTest(const sp<IPreparedModel>& preparedModel, const TestModel& testModel,
-                      const Request& request, bool synchronous, DeadlineBoundType deadlineBound) {
+                      const Request& request, const ExecutionContext& context, bool synchronous,
+                      DeadlineBoundType deadlineBound) {
     const ExecutionFunction execute = synchronous ? executeSynchronously : executeAsynchronously;
     const auto deadline = makeDeadline(deadlineBound);
 
@@ -261,7 +262,7 @@
     // Retrieve execution results.
     ASSERT_TRUE(nn::compliantWithV1_0(request));
     const V1_0::Request request10 = nn::convertToV1_0(request);
-    const std::vector<TestBuffer> outputs = getOutputBuffers(request10);
+    const std::vector<TestBuffer> outputs = context.getOutputBuffers(request10);
 
     // We want "close-enough" results.
     if (status == ErrorStatus::NONE) {
@@ -270,10 +271,11 @@
 }
 
 void runExecutionTests(const sp<IPreparedModel>& preparedModel, const TestModel& testModel,
-                       const Request& request) {
+                       const Request& request, const ExecutionContext& context) {
     for (bool synchronous : {false, true}) {
         for (auto deadlineBound : deadlineBounds) {
-            runExecutionTest(preparedModel, testModel, request, synchronous, deadlineBound);
+            runExecutionTest(preparedModel, testModel, request, context, synchronous,
+                             deadlineBound);
         }
     }
 }
@@ -291,8 +293,9 @@
     if (preparedModel == nullptr) return;
 
     // run execution tests
-    const Request request = nn::convertToV1_3(createRequest(testModel));
-    runExecutionTests(preparedModel, testModel, request);
+    ExecutionContext context;
+    const Request request = nn::convertToV1_3(context.createRequest(testModel));
+    runExecutionTests(preparedModel, testModel, request, context);
 }
 
 class DeadlineTest : public GeneratedTestBase {};
diff --git a/neuralnetworks/1.3/vts/functional/VtsHalNeuralnetworks.cpp b/neuralnetworks/1.3/vts/functional/VtsHalNeuralnetworks.cpp
index 5b07034..df1e453 100644
--- a/neuralnetworks/1.3/vts/functional/VtsHalNeuralnetworks.cpp
+++ b/neuralnetworks/1.3/vts/functional/VtsHalNeuralnetworks.cpp
@@ -177,7 +177,8 @@
 
 TEST_P(ValidationTest, Test) {
     const Model model = createModel(kTestModel);
-    const Request request = nn::convertToV1_3(createRequest(kTestModel));
+    ExecutionContext context;
+    const Request request = nn::convertToV1_3(context.createRequest(kTestModel));
     if (kTestModel.expectFailure) {
         validateFailure(kDevice, model, request);
     } else {
@@ -185,11 +186,31 @@
     }
 }
 
-INSTANTIATE_GENERATED_TEST(ValidationTest, [](const test_helper::TestModel&) { return true; });
+INSTANTIATE_GENERATED_TEST(ValidationTest, [](const std::string& testName) {
+    // Skip validation for the "inputs_as_internal" and "all_tensors_as_inputs"
+    // generated tests.
+    return testName.find("inputs_as_internal") == std::string::npos &&
+           testName.find("all_tensors_as_inputs") == std::string::npos;
+});
 
 sp<IPreparedModel> getPreparedModel_1_3(const sp<PreparedModelCallback>& callback) {
     sp<V1_0::IPreparedModel> preparedModelV1_0 = callback->getPreparedModel();
     return IPreparedModel::castFrom(preparedModelV1_0).withDefault(nullptr);
 }
 
+std::string toString(Executor executor) {
+    switch (executor) {
+        case Executor::ASYNC:
+            return "ASYNC";
+        case Executor::SYNC:
+            return "SYNC";
+        case Executor::BURST:
+            return "BURST";
+        case Executor::FENCED:
+            return "FENCED";
+        default:
+            CHECK(false);
+    }
+}
+
 }  // namespace android::hardware::neuralnetworks::V1_3::vts::functional
diff --git a/neuralnetworks/1.3/vts/functional/VtsHalNeuralnetworks.h b/neuralnetworks/1.3/vts/functional/VtsHalNeuralnetworks.h
index 4e51052..de082c3 100644
--- a/neuralnetworks/1.3/vts/functional/VtsHalNeuralnetworks.h
+++ b/neuralnetworks/1.3/vts/functional/VtsHalNeuralnetworks.h
@@ -52,6 +52,10 @@
 // Utility function to get PreparedModel from callback and downcast to V1_2.
 sp<IPreparedModel> getPreparedModel_1_3(const sp<implementation::PreparedModelCallback>& callback);
 
+enum class Executor { ASYNC, SYNC, BURST, FENCED };
+
+std::string toString(Executor executor);
+
 }  // namespace android::hardware::neuralnetworks::V1_3::vts::functional
 
 #endif  // ANDROID_HARDWARE_NEURALNETWORKS_V1_3_VTS_HAL_NEURALNETWORKS_H