diff --git a/automotive/vehicle/2.0/types.hal b/automotive/vehicle/2.0/types.hal
index b04d096..661c3d4 100644
--- a/automotive/vehicle/2.0/types.hal
+++ b/automotive/vehicle/2.0/types.hal
@@ -3249,6 +3249,16 @@
  */
 enum VmsMessageType : int32_t {
     /**
+     * A notification indicating that the sender has been reset.
+     *
+     * The receiving party must reset its internal state and respond to the
+     * sender with a START_SESSION message as acknowledgement.
+     *
+     * This message type uses enum VmsStartSessionMessageIntegerValuesIndex.
+     */
+    START_SESSION = 17,
+
+    /**
      * A request from the subscribers to the VMS service to subscribe to a layer.
      *
      * This message type uses enum VmsMessageWithLayerIntegerValuesIndex.
@@ -3364,7 +3374,7 @@
      */
     PUBLISHER_INFORMATION_RESPONSE = 16,
 
-    LAST_VMS_MESSAGE_TYPE = PUBLISHER_INFORMATION_RESPONSE,
+    LAST_VMS_MESSAGE_TYPE = START_SESSION,
 };
 
 /**
@@ -3378,6 +3388,30 @@
 };
 
 /*
+ * Handshake data sent as part of a VmsMessageType.START_SESSION message.
+ *
+ * A new session is initiated by sending a START_SESSION message with the
+ * sender's identifier populated and the receiver's identifier set to -1.
+ *
+ * Identifier values are independently generated, but must be non-negative, and
+ * increase monotonically between reboots.
+ *
+ * Upon receiving a START_SESSION with a mis-matching identifier, the receiver
+ * must clear any cached VMS offering or subscription state and acknowledge the
+ * new session by responding with a START_SESSION message that populates both
+ * identifier fields.
+ *
+ * Any VMS messages received between initiation and completion of the handshake
+ * must be discarded.
+ */
+enum VmsStartSessionMessageIntegerValuesIndex : VmsBaseMessageIntegerValuesIndex {
+    /* Identifier field for the Android system service. */
+    SERVICE_ID = 1,
+    /* Identifier field for the HAL client process. */
+    CLIENT_ID = 2,
+};
+
+/*
  * A VMS message with a layer is sent as part of a VmsMessageType.SUBSCRIBE or
  * VmsMessageType.UNSUBSCRIBE messages.
  *
diff --git a/current.txt b/current.txt
index 1f32263..64fd4ae 100644
--- a/current.txt
+++ b/current.txt
@@ -393,8 +393,10 @@
 23780340c686ee86986aa5a9755c2d8566224fed177bbb22a5ebf06be574b60c android.hardware.camera.metadata@3.3::types
 05d1ee760d81cdd2dc7a70ce0241af9fa830edae33b4be83d9bf5fffe05ddc6f android.hardware.camera.provider@2.4::ICameraProvider
 da33234403ff5d60f3473711917b9948e6484a4260b5247acdafb111193a9de2 android.hardware.configstore@1.0::ISurfaceFlingerConfigs
+ede69710c3a95c2cbe818e6c8bb72c7816823face5fc21c17731b26f41d94d65 android.hardware.gnss@1.0::IGnss
 21165b8e30c4b2d52980e4728f661420adc16e38bbe73476c06b2085be908f4c android.hardware.gnss@1.0::IGnssCallback
 d702fb01dc2a0733aa820b7eb65435ee3334f75632ef880bafd2fb8803a20a58 android.hardware.gnss@1.0::IGnssMeasurementCallback
+b5f1f4c1bd6de71a8e71d70f57cdab904ac024a12f3dee3e2173770a4583bcc2 android.hardware.gnss@1.1::IGnss
 7c7721c0f773fcf422b71a4f558545e9e36acc973e58ca51e5bd53905cf46bc0 android.hardware.graphics.bufferqueue@1.0::IGraphicBufferProducer
 d4fea995378bb4f421b4e24ccf68cad2734ab07fe4f874a126ba558b99df5766 android.hardware.graphics.composer@2.1::IComposerClient
 f7d7cb747dc01a9fdb2d39a80003b4d8df9be733d65f5842198802eb6209db69 android.hardware.graphics.mapper@2.0::IMapper
@@ -467,7 +469,7 @@
 7f460e795f5d1ed5e378935f98c6db4d39497de988aef1b4c2a4a07a6c400392 android.hardware.gnss@2.0::IAGnss
 2e5ad983734069e84a760004b32da0d09e4170c05380abe27e6eb80e4aa70d5a android.hardware.gnss@2.0::IAGnssCallback
 1f4ac068a88a72360280d94a7f6fd7c63813c1eea4891a0eb01394d3e7e775f2 android.hardware.gnss@2.0::IAGnssRil
-4deafcdcffa2d002119e7f58810b767a84666e76475aae68e757ec2845d9756d android.hardware.gnss@2.0::IGnss
+f5605f48c2fb9f231615dd932bf730ae9540f4f98b5b7ae2b269975f452f6d73 android.hardware.gnss@2.0::IGnss
 db6bdf6dfc5edf6c85d2944976db899227abb51079c893874353c322342c50b6 android.hardware.gnss@2.0::IGnssBatching
 1f89392f1ebb693d8fa6f50324b1635fc79fab246d31900e63998e1b0e17511c android.hardware.gnss@2.0::IGnssBatchingCallback
 64232037109a5e5f53ab0377e755ec494ae93fcb5279e6eea71dec2e7ac6fbfc android.hardware.gnss@2.0::IGnssCallback
diff --git a/gnss/1.0/IGnss.hal b/gnss/1.0/IGnss.hal
index 602c615..d32bc63 100644
--- a/gnss/1.0/IGnss.hal
+++ b/gnss/1.0/IGnss.hal
@@ -75,8 +75,13 @@
     };
 
     /**
-     * Opens the interface and provides the callback routines
-     * to the implementation of this interface.
+     * Opens the interface and provides the callback routines to the implementation of this
+     * interface.
+     *
+     * The framework calls this method to instruct the GPS engine to prepare for serving requests
+     * from the framework. The GNSS HAL implementation must respond to all GNSS requests from the
+     * framework upon successful return from this method until cleanup() method is called to
+     * close this interface.
      *
      * @param callback Callback interface for IGnss.
      *
@@ -105,6 +110,18 @@
 
     /**
      * Closes the interface.
+     *
+     * The cleanup() method is called by the framework to tell the GNSS HAL implementation to
+     * not expect any GNSS requests in the immediate future - e.g. this may be called when
+     * location is disabled by a user setting or low battery conditions. The GNSS HAL
+     * implementation must immediately stop responding to any existing requests until the
+     * setCallback() method is called again and the requests are re-initiated by the framework.
+     *
+     * After this method is called, the GNSS HAL implementation may choose to modify GNSS hardware
+     * states to save power. It is expected that when setCallback() method is called again to
+     * reopen this interface, to serve requests, there may be some minor delays in GNSS response
+     * requests as hardware readiness states are restored, not to exceed those that occur on normal
+     * device boot up.
      */
     cleanup();
 
@@ -153,7 +170,7 @@
      * @param mode  Parameter must be one of MS_BASED or STANDALONE.
      * It is allowed by the platform (and it is recommended) to fallback to
      * MS_BASED if MS_ASSISTED is passed in, and MS_BASED is supported.
-     * @recurrence GNSS postion recurrence value, either periodic or single.
+     * @recurrence GNSS position recurrence value, either periodic or single.
      * @param minIntervalMs Represents the time between fixes in milliseconds.
      * @param preferredAccuracyMeters Represents the requested fix accuracy in meters.
      * @param preferredTimeMs Represents the requested time to first fix in milliseconds.
diff --git a/gnss/1.1/IGnss.hal b/gnss/1.1/IGnss.hal
index 672f742..3400807 100644
--- a/gnss/1.1/IGnss.hal
+++ b/gnss/1.1/IGnss.hal
@@ -29,6 +29,11 @@
      * Opens the interface and provides the callback routines to the implementation of this
      * interface.
      *
+     * The framework calls this method to instruct the GPS engine to prepare for serving requests
+     * from the framework. The GNSS HAL implementation must respond to all GNSS requests from the
+     * framework upon successful return from this method until cleanup() method is called to
+     * close this interface.
+     *
      * @param callback Callback interface for IGnss.
      *
      * @return success Returns true on success.
@@ -42,7 +47,7 @@
      * @param mode Parameter must be one of MS_BASED or STANDALONE. It is allowed by the platform
      *     (and it is recommended) to fallback to MS_BASED if MS_ASSISTED is passed in, and MS_BASED
      *     is supported.
-     * @param recurrence GNSS postion recurrence value, either periodic or single.
+     * @param recurrence GNSS position recurrence value, either periodic or single.
      * @param minIntervalMs Represents the time between fixes in milliseconds.
      * @param preferredAccuracyMeters Represents the requested fix accuracy in meters.
      * @param preferredTimeMs Represents the requested time to first fix in milliseconds.
diff --git a/gnss/2.0/IGnss.hal b/gnss/2.0/IGnss.hal
index f19f8d0..9935bf9 100644
--- a/gnss/2.0/IGnss.hal
+++ b/gnss/2.0/IGnss.hal
@@ -36,13 +36,18 @@
  * the interface @1.0::IGnssNi.hal and @1.0::IGnssNiCallback.hal are deprecated in this version
  * and are not supported by the framework. The GNSS HAL implementation of this interface
  * must return nullptr for the following @1.0::IGnss method.
- *      getExtensionGnssNi() generates (IGnssNi gnssNiIface);
+ *     getExtensionGnssNi() generates (IGnssNi gnssNiIface);
  */
 interface IGnss extends @1.1::IGnss {
     /**
      * Opens the interface and provides the callback routines to the implementation of this
      * interface.
      *
+     * The framework calls this method to instruct the GPS engine to prepare for serving requests
+     * from the framework. The GNSS HAL implementation must respond to all GNSS requests from the
+     * framework upon successful return from this method until cleanup() method is called to
+     * close this interface.
+     *
      * @param callback Callback interface for IGnss.
      *
      * @return success Returns true on success.
@@ -83,8 +88,9 @@
     /**
      * This method returns the IGnssMeasurement interface.
      *
-     * Exactly one of getExtensionGnssMeasurement_1_1() and getExtensionGnssMeasurement_2_0() must
-     * return a non-null handle, and the other method must return nullptr.
+     * Exactly one of getExtensionGnssMeasurement(), getExtensionGnssMeasurement_1_1(), and
+     * getExtensionGnssMeasurement_2_0() methods must return a non-null handle, and the other
+     * methods must return nullptr.
      *
      * @return gnssMeasurementIface Handle to the IGnssMeasurement interface.
      */
diff --git a/neuralnetworks/1.2/vts/functional/CompilationCachingTests.cpp b/neuralnetworks/1.2/vts/functional/CompilationCachingTests.cpp
index bf91560..4411b90 100644
--- a/neuralnetworks/1.2/vts/functional/CompilationCachingTests.cpp
+++ b/neuralnetworks/1.2/vts/functional/CompilationCachingTests.cpp
@@ -45,9 +45,9 @@
 using ::android::nn::allocateSharedMemory;
 using ::test_helper::MixedTypedExample;
 
-namespace {
+namespace float32_model {
 
-// In frameworks/ml/nn/runtime/test/generated/, creates a hidl model of mobilenet.
+// In frameworks/ml/nn/runtime/test/generated/, creates a hidl model of float32 mobilenet.
 #include "examples/mobilenet_224_gender_basic_fixed.example.cpp"
 #include "vts_models/mobilenet_224_gender_basic_fixed.model.cpp"
 
@@ -55,6 +55,44 @@
 [[maybe_unused]] auto dummy_createTestModel = createTestModel_dynamic_output_shape;
 [[maybe_unused]] auto dummy_get_examples = get_examples_dynamic_output_shape;
 
+// MixedTypedExample is defined in frameworks/ml/nn/tools/test_generator/include/TestHarness.h.
+// This function assumes the operation is always ADD.
+std::vector<MixedTypedExample> getLargeModelExamples(uint32_t len) {
+    float outputValue = 1.0f + static_cast<float>(len);
+    return {{.operands = {
+                     // Input
+                     {.operandDimensions = {{0, {1}}}, .float32Operands = {{0, {1.0f}}}},
+                     // Output
+                     {.operandDimensions = {{0, {1}}}, .float32Operands = {{0, {outputValue}}}}}}};
+}
+
+}  // namespace float32_model
+
+namespace quant8_model {
+
+// In frameworks/ml/nn/runtime/test/generated/, creates a hidl model of quant8 mobilenet.
+#include "examples/mobilenet_quantized.example.cpp"
+#include "vts_models/mobilenet_quantized.model.cpp"
+
+// Prevent the compiler from complaining about an otherwise unused function.
+[[maybe_unused]] auto dummy_createTestModel = createTestModel_dynamic_output_shape;
+[[maybe_unused]] auto dummy_get_examples = get_examples_dynamic_output_shape;
+
+// MixedTypedExample is defined in frameworks/ml/nn/tools/test_generator/include/TestHarness.h.
+// This function assumes the operation is always ADD.
+std::vector<MixedTypedExample> getLargeModelExamples(uint32_t len) {
+    uint8_t outputValue = 1 + static_cast<uint8_t>(len);
+    return {{.operands = {// Input
+                          {.operandDimensions = {{0, {1}}}, .quant8AsymmOperands = {{0, {1}}}},
+                          // Output
+                          {.operandDimensions = {{0, {1}}},
+                           .quant8AsymmOperands = {{0, {outputValue}}}}}}};
+}
+
+}  // namespace quant8_model
+
+namespace {
+
 enum class AccessMode { READ_WRITE, READ_ONLY, WRITE_ONLY };
 
 // Creates cache handles based on provided file groups.
@@ -101,14 +139,18 @@
 //                ↑      ↑      ↑             ↑
 //               [1]    [1]    [1]           [1]
 //
-Model createLargeTestModel(OperationType op, uint32_t len) {
+// This function assumes the operation is either ADD or MUL.
+template <typename CppType, OperandType operandType>
+Model createLargeTestModelImpl(OperationType op, uint32_t len) {
+    EXPECT_TRUE(op == OperationType::ADD || op == OperationType::MUL);
+
     // Model operations and operands.
     std::vector<Operation> operations(len);
     std::vector<Operand> operands(len * 2 + 2);
 
     // The constant buffer pool. This contains the activation scalar, followed by the
     // per-operation constant operands.
-    std::vector<uint8_t> operandValues(sizeof(int32_t) + len * sizeof(float));
+    std::vector<uint8_t> operandValues(sizeof(int32_t) + len * sizeof(CppType));
 
     // The activation scalar, value = 0.
     operands[0] = {
@@ -122,7 +164,26 @@
     };
     memset(operandValues.data(), 0, sizeof(int32_t));
 
-    const float floatBufferValue = 1.0f;
+    // The buffer value of the constant second operand. The logical value is always 1.0f.
+    CppType bufferValue;
+    // The scale of the first and second operand.
+    float scale1, scale2;
+    if (operandType == OperandType::TENSOR_FLOAT32) {
+        bufferValue = 1.0f;
+        scale1 = 0.0f;
+        scale2 = 0.0f;
+    } else if (op == OperationType::ADD) {
+        bufferValue = 1;
+        scale1 = 1.0f;
+        scale2 = 1.0f;
+    } else {
+        // To satisfy the constraint on quant8 MUL: input0.scale * input1.scale < output.scale,
+        // set input1 to have scale = 0.5f and bufferValue = 2, i.e. 1.0f in floating point.
+        bufferValue = 2;
+        scale1 = 1.0f;
+        scale2 = 0.5f;
+    }
+
     for (uint32_t i = 0; i < len; i++) {
         const uint32_t firstInputIndex = i * 2 + 1;
         const uint32_t secondInputIndex = firstInputIndex + 1;
@@ -130,10 +191,10 @@
 
         // The first operation input.
         operands[firstInputIndex] = {
-                .type = OperandType::TENSOR_FLOAT32,
+                .type = operandType,
                 .dimensions = {1},
                 .numberOfConsumers = 1,
-                .scale = 0.0f,
+                .scale = scale1,
                 .zeroPoint = 0,
                 .lifetime = (i == 0 ? OperandLifeTime::MODEL_INPUT
                                     : OperandLifeTime::TEMPORARY_VARIABLE),
@@ -142,18 +203,18 @@
 
         // The second operation input, value = 1.
         operands[secondInputIndex] = {
-                .type = OperandType::TENSOR_FLOAT32,
+                .type = operandType,
                 .dimensions = {1},
                 .numberOfConsumers = 1,
-                .scale = 0.0f,
+                .scale = scale2,
                 .zeroPoint = 0,
                 .lifetime = OperandLifeTime::CONSTANT_COPY,
                 .location = {.poolIndex = 0,
-                             .offset = static_cast<uint32_t>(i * sizeof(float) + sizeof(int32_t)),
-                             .length = sizeof(float)},
+                             .offset = static_cast<uint32_t>(i * sizeof(CppType) + sizeof(int32_t)),
+                             .length = sizeof(CppType)},
         };
-        memcpy(operandValues.data() + sizeof(int32_t) + i * sizeof(float), &floatBufferValue,
-               sizeof(float));
+        memcpy(operandValues.data() + sizeof(int32_t) + i * sizeof(CppType), &bufferValue,
+               sizeof(CppType));
 
         // The operation. All operations share the same activation scalar.
         // The output operand is created as an input in the next iteration of the loop, in the case
@@ -168,10 +229,10 @@
 
     // The model output.
     operands.back() = {
-            .type = OperandType::TENSOR_FLOAT32,
+            .type = operandType,
             .dimensions = {1},
             .numberOfConsumers = 0,
-            .scale = 0.0f,
+            .scale = scale1,
             .zeroPoint = 0,
             .lifetime = OperandLifeTime::MODEL_OUTPUT,
             .location = {},
@@ -191,22 +252,13 @@
     };
 }
 
-// MixedTypedExample is defined in frameworks/ml/nn/tools/test_generator/include/TestHarness.h.
-// This function assumes the operation is always ADD.
-std::vector<MixedTypedExample> getLargeModelExamples(uint32_t len) {
-    float outputValue = 1.0f + static_cast<float>(len);
-    return {{.operands = {
-                     // Input
-                     {.operandDimensions = {{0, {1}}}, .float32Operands = {{0, {1.0f}}}},
-                     // Output
-                     {.operandDimensions = {{0, {1}}}, .float32Operands = {{0, {outputValue}}}}}}};
-};
-
 }  // namespace
 
 // Tag for the compilation caching tests.
-class CompilationCachingTest : public NeuralnetworksHidlTest {
+class CompilationCachingTestBase : public NeuralnetworksHidlTest {
   protected:
+    CompilationCachingTestBase(OperandType type) : kOperandType(type) {}
+
     void SetUp() override {
         NeuralnetworksHidlTest::SetUp();
         ASSERT_NE(device.get(), nullptr);
@@ -263,6 +315,40 @@
         NeuralnetworksHidlTest::TearDown();
     }
 
+    // Model and examples creators. According to kOperandType, the following methods will return
+    // either float32 model/examples or the quant8 variant.
+    Model createTestModel() {
+        if (kOperandType == OperandType::TENSOR_FLOAT32) {
+            return float32_model::createTestModel();
+        } else {
+            return quant8_model::createTestModel();
+        }
+    }
+
+    std::vector<MixedTypedExample> get_examples() {
+        if (kOperandType == OperandType::TENSOR_FLOAT32) {
+            return float32_model::get_examples();
+        } else {
+            return quant8_model::get_examples();
+        }
+    }
+
+    Model createLargeTestModel(OperationType op, uint32_t len) {
+        if (kOperandType == OperandType::TENSOR_FLOAT32) {
+            return createLargeTestModelImpl<float, OperandType::TENSOR_FLOAT32>(op, len);
+        } else {
+            return createLargeTestModelImpl<uint8_t, OperandType::TENSOR_QUANT8_ASYMM>(op, len);
+        }
+    }
+
+    std::vector<MixedTypedExample> getLargeModelExamples(uint32_t len) {
+        if (kOperandType == OperandType::TENSOR_FLOAT32) {
+            return float32_model::getLargeModelExamples(len);
+        } else {
+            return quant8_model::getLargeModelExamples(len);
+        }
+    }
+
     // See if the service can handle the model.
     bool isModelFullySupported(const V1_2::Model& model) {
         bool fullySupportsModel = false;
@@ -366,9 +452,20 @@
     uint32_t mNumModelCache;
     uint32_t mNumDataCache;
     uint32_t mIsCachingSupported;
+
+    // The primary data type of the testModel.
+    const OperandType kOperandType;
 };
 
-TEST_F(CompilationCachingTest, CacheSavingAndRetrieval) {
+// A parameterized fixture of CompilationCachingTestBase. Every test will run twice, with the first
+// pass running with float32 models and the second pass running with quant8 models.
+class CompilationCachingTest : public CompilationCachingTestBase,
+                               public ::testing::WithParamInterface<OperandType> {
+  protected:
+    CompilationCachingTest() : CompilationCachingTestBase(GetParam()) {}
+};
+
+TEST_P(CompilationCachingTest, CacheSavingAndRetrieval) {
     // Create test HIDL model and compile.
     const Model testModel = createTestModel();
     if (checkEarlyTermination(testModel)) return;
@@ -409,7 +506,7 @@
                                            /*testDynamicOutputShape=*/false);
 }
 
-TEST_F(CompilationCachingTest, CacheSavingAndRetrievalNonZeroOffset) {
+TEST_P(CompilationCachingTest, CacheSavingAndRetrievalNonZeroOffset) {
     // Create test HIDL model and compile.
     const Model testModel = createTestModel();
     if (checkEarlyTermination(testModel)) return;
@@ -472,7 +569,7 @@
                                            /*testDynamicOutputShape=*/false);
 }
 
-TEST_F(CompilationCachingTest, SaveToCacheInvalidNumCache) {
+TEST_P(CompilationCachingTest, SaveToCacheInvalidNumCache) {
     // Create test HIDL model and compile.
     const Model testModel = createTestModel();
     if (checkEarlyTermination(testModel)) return;
@@ -584,7 +681,7 @@
     }
 }
 
-TEST_F(CompilationCachingTest, PrepareModelFromCacheInvalidNumCache) {
+TEST_P(CompilationCachingTest, PrepareModelFromCacheInvalidNumCache) {
     // Create test HIDL model and compile.
     const Model testModel = createTestModel();
     if (checkEarlyTermination(testModel)) return;
@@ -664,7 +761,7 @@
     }
 }
 
-TEST_F(CompilationCachingTest, SaveToCacheInvalidNumFd) {
+TEST_P(CompilationCachingTest, SaveToCacheInvalidNumFd) {
     // Create test HIDL model and compile.
     const Model testModel = createTestModel();
     if (checkEarlyTermination(testModel)) return;
@@ -776,7 +873,7 @@
     }
 }
 
-TEST_F(CompilationCachingTest, PrepareModelFromCacheInvalidNumFd) {
+TEST_P(CompilationCachingTest, PrepareModelFromCacheInvalidNumFd) {
     // Create test HIDL model and compile.
     const Model testModel = createTestModel();
     if (checkEarlyTermination(testModel)) return;
@@ -856,7 +953,7 @@
     }
 }
 
-TEST_F(CompilationCachingTest, SaveToCacheInvalidAccessMode) {
+TEST_P(CompilationCachingTest, SaveToCacheInvalidAccessMode) {
     // Create test HIDL model and compile.
     const Model testModel = createTestModel();
     if (checkEarlyTermination(testModel)) return;
@@ -914,7 +1011,7 @@
     }
 }
 
-TEST_F(CompilationCachingTest, PrepareModelFromCacheInvalidAccessMode) {
+TEST_P(CompilationCachingTest, PrepareModelFromCacheInvalidAccessMode) {
     // Create test HIDL model and compile.
     const Model testModel = createTestModel();
     if (checkEarlyTermination(testModel)) return;
@@ -990,7 +1087,7 @@
 constexpr uint32_t kLargeModelSize = 100;
 constexpr uint32_t kNumIterationsTOCTOU = 100;
 
-TEST_F(CompilationCachingTest, SaveToCache_TOCTOU) {
+TEST_P(CompilationCachingTest, SaveToCache_TOCTOU) {
     if (!mIsCachingSupported) return;
 
     // Create test models and check if fully supported by the service.
@@ -1053,7 +1150,7 @@
     }
 }
 
-TEST_F(CompilationCachingTest, PrepareFromCache_TOCTOU) {
+TEST_P(CompilationCachingTest, PrepareFromCache_TOCTOU) {
     if (!mIsCachingSupported) return;
 
     // Create test models and check if fully supported by the service.
@@ -1116,7 +1213,7 @@
     }
 }
 
-TEST_F(CompilationCachingTest, ReplaceSecuritySensitiveCache) {
+TEST_P(CompilationCachingTest, ReplaceSecuritySensitiveCache) {
     if (!mIsCachingSupported) return;
 
     // Create test models and check if fully supported by the service.
@@ -1164,11 +1261,19 @@
     }
 }
 
-class CompilationCachingSecurityTest : public CompilationCachingTest,
-                                       public ::testing::WithParamInterface<uint32_t> {
+static const auto kOperandTypeChoices =
+        ::testing::Values(OperandType::TENSOR_FLOAT32, OperandType::TENSOR_QUANT8_ASYMM);
+
+INSTANTIATE_TEST_CASE_P(TestCompilationCaching, CompilationCachingTest, kOperandTypeChoices);
+
+class CompilationCachingSecurityTest
+    : public CompilationCachingTestBase,
+      public ::testing::WithParamInterface<std::tuple<OperandType, uint32_t>> {
   protected:
+    CompilationCachingSecurityTest() : CompilationCachingTestBase(std::get<0>(GetParam())) {}
+
     void SetUp() {
-        CompilationCachingTest::SetUp();
+        CompilationCachingTestBase::SetUp();
         generator.seed(kSeed);
     }
 
@@ -1254,7 +1359,7 @@
         }
     }
 
-    const uint32_t kSeed = GetParam();
+    const uint32_t kSeed = std::get<1>(GetParam());
     std::mt19937 generator;
 };
 
@@ -1302,7 +1407,7 @@
 }
 
 INSTANTIATE_TEST_CASE_P(TestCompilationCaching, CompilationCachingSecurityTest,
-                        ::testing::Range(0U, 10U));
+                        ::testing::Combine(kOperandTypeChoices, ::testing::Range(0U, 10U)));
 
 }  // namespace functional
 }  // namespace vts