diff --git a/neuralnetworks/1.0/vts/functional/GeneratedTestHarness.cpp b/neuralnetworks/1.0/vts/functional/GeneratedTestHarness.cpp
index b5a8607..de0e494 100644
--- a/neuralnetworks/1.0/vts/functional/GeneratedTestHarness.cpp
+++ b/neuralnetworks/1.0/vts/functional/GeneratedTestHarness.cpp
@@ -51,14 +51,13 @@
 using ::test_helper::Int32Operands;
 using ::test_helper::MixedTyped;
 using ::test_helper::MixedTypedExample;
-using ::test_helper::MixedTypedIndex;
 using ::test_helper::Quant8Operands;
 using ::test_helper::resize_accordingly;
 
 template <typename T>
-void copy_back_(MixedTyped* dst, const std::vector<RequestArgument>& ra, char* src) {
-    MixedTyped& test = *dst;
-    for_each<T>(test, [&ra, src](int index, std::vector<T>& m) {
+void copy_back_(std::map<int, std::vector<T>>* dst, const std::vector<RequestArgument>& ra,
+                char* src) {
+    for_each<T>(*dst, [&ra, src](int index, std::vector<T>& m) {
         ASSERT_EQ(m.size(), ra[index].location.length / sizeof(T));
         char* begin = src + ra[index].location.offset;
         memcpy(m.data(), begin, ra[index].location.length);
@@ -66,14 +65,14 @@
 }
 
 void copy_back(MixedTyped* dst, const std::vector<RequestArgument>& ra, char* src) {
-    copy_back_<float>(dst, ra, src);
-    copy_back_<int32_t>(dst, ra, src);
-    copy_back_<uint8_t>(dst, ra, src);
-    copy_back_<int16_t>(dst, ra, src);
-    copy_back_<_Float16>(dst, ra, src);
-    copy_back_<bool8>(dst, ra, src);
-    copy_back_<int8_t>(dst, ra, src);
-    static_assert(7 == std::tuple_size<MixedTyped>::value,
+    copy_back_(&dst->float32Operands, ra, src);
+    copy_back_(&dst->int32Operands, ra, src);
+    copy_back_(&dst->quant8Operands, ra, src);
+    copy_back_(&dst->quant16Operands, ra, src);
+    copy_back_(&dst->float16Operands, ra, src);
+    copy_back_(&dst->bool8Operands, ra, src);
+    copy_back_(&dst->quant8ChannelOperands, ra, src);
+    static_assert(7 == MixedTyped::kNumTypes,
                   "Number of types in MixedTyped changed, but copy_back function wasn't updated");
 }
 
@@ -115,7 +114,8 @@
 void EvaluatePreparedModel(sp<T_IPreparedModel>& preparedModel, std::function<bool(int)> is_ignored,
                            const std::vector<MixedTypedExample>& examples,
                            bool hasRelaxedFloat32Model = false, float fpAtol = kDefaultAtol,
-                           float fpRtol = kDefaultRtol, Synchronously sync = Synchronously::NO) {
+                           float fpRtol = kDefaultRtol, Synchronously sync = Synchronously::NO,
+                           bool testDynamicOutputShape = false) {
     const uint32_t INPUT = 0;
     const uint32_t OUTPUT = 1;
 
@@ -125,7 +125,7 @@
         const MixedTyped& inputs = example.operands.first;
         const MixedTyped& golden = example.operands.second;
 
-        const bool hasFloat16Inputs = !std::get<MixedTypedIndex<_Float16>::index>(inputs).empty();
+        const bool hasFloat16Inputs = !inputs.float16Operands.empty();
         if (hasRelaxedFloat32Model || hasFloat16Inputs) {
             // TODO: Adjust the error limit based on testing.
             // If in relaxed mode, set the absolute tolerance to be 5ULP of FP16.
@@ -237,10 +237,24 @@
             executionStatus = static_cast<ErrorStatus>(executionReturnStatus);
         }
 
+        if (testDynamicOutputShape && executionStatus != ErrorStatus::NONE) {
+            LOG(INFO) << "NN VTS: Early termination of test because vendor service cannot "
+                         "execute model that it does not support.";
+            std::cout << "[          ]   Early termination of test because vendor service cannot "
+                         "execute model that it does not support."
+                      << std::endl;
+            return;
+        }
         ASSERT_EQ(ErrorStatus::NONE, executionStatus);
-        // TODO(xusongw): Check if the returned output shapes match with expectation once the
-        //                sample driver implementation of dynamic output shape is finished.
-        ASSERT_EQ(outputShapes.size(), 0);
+
+        // Go through all outputs, overwrite output dimensions with returned output shapes
+        if (testDynamicOutputShape) {
+            ASSERT_NE(outputShapes.size(), 0);
+            for_each<uint32_t>(test.operandDimensions,
+                               [&outputShapes](int idx, std::vector<uint32_t>& dim) {
+                                   dim = outputShapes[idx].dimensions;
+                               });
+        }
 
         // validate results
         outputMemory->read();
@@ -261,9 +275,10 @@
 template <typename T_IPreparedModel>
 void EvaluatePreparedModel(sp<T_IPreparedModel>& preparedModel, std::function<bool(int)> is_ignored,
                            const std::vector<MixedTypedExample>& examples,
-                           bool hasRelaxedFloat32Model, Synchronously sync) {
+                           bool hasRelaxedFloat32Model, Synchronously sync,
+                           bool testDynamicOutputShape) {
     EvaluatePreparedModel(preparedModel, is_ignored, examples, hasRelaxedFloat32Model, kDefaultAtol,
-                          kDefaultRtol, sync);
+                          kDefaultRtol, sync, testDynamicOutputShape);
 }
 
 static void getPreparedModel(sp<PreparedModelCallback> callback,
@@ -319,7 +334,8 @@
 
     float fpAtol = 1e-5f, fpRtol = 5.0f * 1.1920928955078125e-7f;
     EvaluatePreparedModel(preparedModel, is_ignored, examples,
-                          /*hasRelaxedFloat32Model=*/false, fpAtol, fpRtol);
+                          /*hasRelaxedFloat32Model=*/false, fpAtol, fpRtol, Synchronously::NO,
+                          /*testDynamicOutputShape=*/false);
 }
 
 void Execute(const sp<V1_1::IDevice>& device, std::function<V1_1::Model(void)> create_model,
@@ -365,12 +381,14 @@
     ASSERT_NE(nullptr, preparedModel.get());
 
     EvaluatePreparedModel(preparedModel, is_ignored, examples,
-                          model.relaxComputationFloat32toFloat16);
+                          model.relaxComputationFloat32toFloat16, 1e-5f, 1e-5f, Synchronously::NO,
+                          /*testDynamicOutputShape=*/false);
 }
 
 // TODO: Reduce code duplication.
 void Execute(const sp<V1_2::IDevice>& device, std::function<V1_2::Model(void)> create_model,
-             std::function<bool(int)> is_ignored, const std::vector<MixedTypedExample>& examples) {
+             std::function<bool(int)> is_ignored, const std::vector<MixedTypedExample>& examples,
+             bool testDynamicOutputShape) {
     V1_2::Model model = create_model();
 
     // see if service can handle model
@@ -412,9 +430,11 @@
     ASSERT_NE(nullptr, preparedModel.get());
 
     EvaluatePreparedModel(preparedModel, is_ignored, examples,
-                          model.relaxComputationFloat32toFloat16, Synchronously::NO);
+                          model.relaxComputationFloat32toFloat16, Synchronously::NO,
+                          testDynamicOutputShape);
     EvaluatePreparedModel(preparedModel, is_ignored, examples,
-                          model.relaxComputationFloat32toFloat16, Synchronously::YES);
+                          model.relaxComputationFloat32toFloat16, Synchronously::YES,
+                          testDynamicOutputShape);
 }
 
 }  // namespace generated_tests
diff --git a/neuralnetworks/1.2/vts/functional/Android.bp b/neuralnetworks/1.2/vts/functional/Android.bp
index 5b119ee..0cb9e16 100644
--- a/neuralnetworks/1.2/vts/functional/Android.bp
+++ b/neuralnetworks/1.2/vts/functional/Android.bp
@@ -21,6 +21,9 @@
     srcs: [
         "GeneratedTestsV1_0.cpp",
     ],
+    cflags: [
+        "-DNN_TEST_DYNAMIC_OUTPUT_SHAPE"
+    ],
     test_suites: ["general-tests"],
 }
 
@@ -31,6 +34,9 @@
     srcs: [
         "GeneratedTestsV1_1.cpp",
     ],
+    cflags: [
+        "-DNN_TEST_DYNAMIC_OUTPUT_SHAPE"
+    ],
     test_suites: ["general-tests"],
 }
 
@@ -42,5 +48,8 @@
         "BasicTests.cpp",
         "GeneratedTests.cpp",
     ],
+    cflags: [
+        "-DNN_TEST_DYNAMIC_OUTPUT_SHAPE"
+    ],
     test_suites: ["general-tests"],
 }
diff --git a/neuralnetworks/1.2/vts/functional/GeneratedTests.cpp b/neuralnetworks/1.2/vts/functional/GeneratedTests.cpp
index 9bff09c..4bc891f 100644
--- a/neuralnetworks/1.2/vts/functional/GeneratedTests.cpp
+++ b/neuralnetworks/1.2/vts/functional/GeneratedTests.cpp
@@ -33,7 +33,8 @@
 namespace generated_tests {
 using ::test_helper::MixedTypedExample;
 extern void Execute(const sp<V1_2::IDevice>&, std::function<V1_2::Model(void)>,
-                    std::function<bool(int)>, const std::vector<MixedTypedExample>&);
+                    std::function<bool(int)>, const std::vector<MixedTypedExample>&,
+                    bool testDynamicOutputShape = false);
 }  // namespace generated_tests
 
 namespace V1_2 {
diff --git a/neuralnetworks/1.2/vts/functional/GeneratedTestsV1_0.cpp b/neuralnetworks/1.2/vts/functional/GeneratedTestsV1_0.cpp
index 56a61d4..956926a 100644
--- a/neuralnetworks/1.2/vts/functional/GeneratedTestsV1_0.cpp
+++ b/neuralnetworks/1.2/vts/functional/GeneratedTestsV1_0.cpp
@@ -33,7 +33,8 @@
 namespace generated_tests {
 using ::test_helper::MixedTypedExample;
 extern void Execute(const sp<V1_2::IDevice>&, std::function<V1_2::Model(void)>,
-                    std::function<bool(int)>, const std::vector<MixedTypedExample>&);
+                    std::function<bool(int)>, const std::vector<MixedTypedExample>&,
+                    bool testDynamicOutputShape = false);
 }  // namespace generated_tests
 
 namespace V1_2 {
diff --git a/neuralnetworks/1.2/vts/functional/GeneratedTestsV1_1.cpp b/neuralnetworks/1.2/vts/functional/GeneratedTestsV1_1.cpp
index 1c781ec..425690f 100644
--- a/neuralnetworks/1.2/vts/functional/GeneratedTestsV1_1.cpp
+++ b/neuralnetworks/1.2/vts/functional/GeneratedTestsV1_1.cpp
@@ -33,7 +33,8 @@
 namespace generated_tests {
 using ::test_helper::MixedTypedExample;
 extern void Execute(const sp<V1_2::IDevice>&, std::function<V1_2::Model(void)>,
-                    std::function<bool(int)>, const std::vector<MixedTypedExample>&);
+                    std::function<bool(int)>, const std::vector<MixedTypedExample>&,
+                    bool testDynamicOutputShape = false);
 }  // namespace generated_tests
 
 namespace V1_2 {
diff --git a/neuralnetworks/1.2/vts/functional/ValidateModel.cpp b/neuralnetworks/1.2/vts/functional/ValidateModel.cpp
index b1a0e53..1f9c99d 100644
--- a/neuralnetworks/1.2/vts/functional/ValidateModel.cpp
+++ b/neuralnetworks/1.2/vts/functional/ValidateModel.cpp
@@ -172,6 +172,9 @@
 static void mutateOperandRankTest(const sp<IDevice>& device, const Model& model) {
     for (size_t operand = 0; operand < model.operands.size(); ++operand) {
         const uint32_t invalidRank = getInvalidRank(model.operands[operand].type);
+        if (invalidRank == 0) {
+            continue;
+        }
         const std::string message = "mutateOperandRankTest: operand " + std::to_string(operand) +
                                     " has rank of " + std::to_string(invalidRank);
         validate(device, message, model, [operand, invalidRank](Model* model) {
diff --git a/neuralnetworks/1.2/vts/functional/VtsHalNeuralnetworks.h b/neuralnetworks/1.2/vts/functional/VtsHalNeuralnetworks.h
index dedab8d..c0c21bd 100644
--- a/neuralnetworks/1.2/vts/functional/VtsHalNeuralnetworks.h
+++ b/neuralnetworks/1.2/vts/functional/VtsHalNeuralnetworks.h
@@ -79,6 +79,9 @@
 // Tag for the generated tests
 class GeneratedTest : public NeuralnetworksHidlTest {};
 
+// Tag for the dynamic output shape tests
+class DynamicOutputShapeTest : public NeuralnetworksHidlTest {};
+
 // Utility function to get PreparedModel from callback and downcast to V1_2.
 sp<IPreparedModel> getPreparedModel_1_2(
     const sp<V1_2::implementation::PreparedModelCallback>& callback);