diff --git a/neuralnetworks/1.1/utils/Android.bp b/neuralnetworks/1.1/utils/Android.bp
new file mode 100644
index 0000000..85a32c5
--- /dev/null
+++ b/neuralnetworks/1.1/utils/Android.bp
@@ -0,0 +1,35 @@
+//
+// 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.
+//
+
+cc_library_static {
+    name: "neuralnetworks_utils_hal_1_1",
+    defaults: ["neuralnetworks_utils_defaults"],
+    srcs: ["src/*"],
+    local_include_dirs: ["include/nnapi/hal/1.1/"],
+    export_include_dirs: ["include"],
+    static_libs: [
+        "neuralnetworks_types",
+        "neuralnetworks_utils_hal_common",
+        "neuralnetworks_utils_hal_1_0",
+    ],
+    shared_libs: [
+        "android.hardware.neuralnetworks@1.0",
+        "android.hardware.neuralnetworks@1.1",
+    ],
+    export_static_lib_headers: [
+        "neuralnetworks_utils_hal_common",
+    ],
+}
diff --git a/neuralnetworks/1.1/utils/OWNERS b/neuralnetworks/1.1/utils/OWNERS
new file mode 100644
index 0000000..e4feee3
--- /dev/null
+++ b/neuralnetworks/1.1/utils/OWNERS
@@ -0,0 +1,11 @@
+# Neuralnetworks team
+butlermichael@google.com
+dgross@google.com
+galarragas@google.com
+jeanluc@google.com
+levp@google.com
+miaowang@google.com
+pszczepaniak@google.com
+slavash@google.com
+vddang@google.com
+xusongw@google.com
diff --git a/neuralnetworks/1.1/utils/include/nnapi/hal/1.1/Conversions.h b/neuralnetworks/1.1/utils/include/nnapi/hal/1.1/Conversions.h
new file mode 100644
index 0000000..d0c5397
--- /dev/null
+++ b/neuralnetworks/1.1/utils/include/nnapi/hal/1.1/Conversions.h
@@ -0,0 +1,45 @@
+/*
+ * 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.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_1_CONVERSIONS_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_1_CONVERSIONS_H
+
+#include <android/hardware/neuralnetworks/1.1/types.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/CommonUtils.h>
+
+namespace android::nn {
+
+Result<OperationType> convert(const hal::V1_1::OperationType& operationType);
+Result<Capabilities> convert(const hal::V1_1::Capabilities& capabilities);
+Result<Operation> convert(const hal::V1_1::Operation& operation);
+Result<Model> convert(const hal::V1_1::Model& model);
+Result<ExecutionPreference> convert(const hal::V1_1::ExecutionPreference& executionPreference);
+
+}  // namespace android::nn
+
+namespace android::hardware::neuralnetworks::V1_1::utils {
+
+nn::Result<OperationType> convert(const nn::OperationType& operationType);
+nn::Result<Capabilities> convert(const nn::Capabilities& capabilities);
+nn::Result<Operation> convert(const nn::Operation& operation);
+nn::Result<Model> convert(const nn::Model& model);
+nn::Result<ExecutionPreference> convert(const nn::ExecutionPreference& executionPreference);
+
+}  // namespace android::hardware::neuralnetworks::V1_1::utils
+
+#endif  // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_1_CONVERSIONS_H
diff --git a/neuralnetworks/1.1/utils/include/nnapi/hal/1.1/Utils.h b/neuralnetworks/1.1/utils/include/nnapi/hal/1.1/Utils.h
new file mode 100644
index 0000000..6f9aa60
--- /dev/null
+++ b/neuralnetworks/1.1/utils/include/nnapi/hal/1.1/Utils.h
@@ -0,0 +1,65 @@
+/*
+ * 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.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_1_UTILS_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_1_UTILS_H
+
+#include "nnapi/hal/1.1/Conversions.h"
+
+#include <android-base/logging.h>
+#include <android/hardware/neuralnetworks/1.1/types.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/Validation.h>
+#include <nnapi/hal/1.0/Conversions.h>
+
+namespace android::hardware::neuralnetworks::V1_1::utils {
+
+constexpr auto kDefaultExecutionPreference = ExecutionPreference::FAST_SINGLE_ANSWER;
+constexpr auto kVersion = nn::Version::ANDROID_P;
+
+template <typename Type>
+nn::Result<void> validate(const Type& halObject) {
+    const auto canonical = NN_TRY(nn::convert(halObject));
+    const auto version = NN_TRY(nn::validate(canonical));
+    if (version > utils::kVersion) {
+        return NN_ERROR() << "";
+    }
+    return {};
+}
+
+template <typename Type>
+bool valid(const Type& halObject) {
+    const auto result = utils::validate(halObject);
+    if (!result.has_value()) {
+        LOG(ERROR) << result.error();
+    }
+    return result.has_value();
+}
+
+template <typename Type>
+decltype(nn::convert(std::declval<Type>())) validatedConvertToCanonical(const Type& halObject) {
+    auto canonical = NN_TRY(nn::convert(halObject));
+    const auto version = NN_TRY(nn::validate(canonical));
+    if (version > utils::kVersion) {
+        return NN_ERROR() << "";
+    }
+    return canonical;
+}
+
+}  // namespace android::hardware::neuralnetworks::V1_1::utils
+
+#endif  // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_1_UTILS_H
diff --git a/neuralnetworks/1.1/utils/src/Assertions.cpp b/neuralnetworks/1.1/utils/src/Assertions.cpp
new file mode 100644
index 0000000..ba4a388
--- /dev/null
+++ b/neuralnetworks/1.1/utils/src/Assertions.cpp
@@ -0,0 +1,100 @@
+/*
+ * 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.
+ */
+
+#include <android/hardware/neuralnetworks/1.1/types.h>
+#include <nnapi/OperandTypes.h>
+#include <nnapi/OperationTypes.h>
+#include <nnapi/Types.h>
+#include <type_traits>
+
+namespace {
+
+#define COMPARE_ENUMS_TYPES(type)                                                                  \
+    static_assert(std::is_same_v<                                                                  \
+                          std::underlying_type_t<::android::hardware::neuralnetworks::V1_1::type>, \
+                          std::underlying_type_t<::android::nn::type>>,                            \
+                  "::android::hardware::neuralnetworks::V1_1::" #type                              \
+                  " does not have the same underlying type as ::android::nn::" #type)
+
+COMPARE_ENUMS_TYPES(OperationType);
+COMPARE_ENUMS_TYPES(ExecutionPreference);
+
+#undef COMPARE_ENUMS_TYPES
+
+#define COMPARE_ENUMS_FULL(symbol, type)                                                          \
+    static_assert(                                                                                \
+            static_cast<std::underlying_type_t<::android::hardware::neuralnetworks::V1_1::type>>( \
+                    ::android::hardware::neuralnetworks::V1_1::type::symbol) ==                   \
+                    static_cast<std::underlying_type_t<::android::nn::type>>(                     \
+                            ::android::nn::type::symbol),                                         \
+            "::android::hardware::neuralnetworks::V1_1::" #type "::" #symbol                      \
+            " does not match ::android::nn::" #type "::" #symbol)
+
+#define COMPARE_ENUMS(symbol) COMPARE_ENUMS_FULL(symbol, OperationType)
+
+COMPARE_ENUMS(ADD);
+COMPARE_ENUMS(AVERAGE_POOL_2D);
+COMPARE_ENUMS(CONCATENATION);
+COMPARE_ENUMS(CONV_2D);
+COMPARE_ENUMS(DEPTHWISE_CONV_2D);
+COMPARE_ENUMS(DEPTH_TO_SPACE);
+COMPARE_ENUMS(DEQUANTIZE);
+COMPARE_ENUMS(EMBEDDING_LOOKUP);
+COMPARE_ENUMS(FLOOR);
+COMPARE_ENUMS(FULLY_CONNECTED);
+COMPARE_ENUMS(HASHTABLE_LOOKUP);
+COMPARE_ENUMS(L2_NORMALIZATION);
+COMPARE_ENUMS(L2_POOL_2D);
+COMPARE_ENUMS(LOCAL_RESPONSE_NORMALIZATION);
+COMPARE_ENUMS(LOGISTIC);
+COMPARE_ENUMS(LSH_PROJECTION);
+COMPARE_ENUMS(LSTM);
+COMPARE_ENUMS(MAX_POOL_2D);
+COMPARE_ENUMS(MUL);
+COMPARE_ENUMS(RELU);
+COMPARE_ENUMS(RELU1);
+COMPARE_ENUMS(RELU6);
+COMPARE_ENUMS(RESHAPE);
+COMPARE_ENUMS(RESIZE_BILINEAR);
+COMPARE_ENUMS(RNN);
+COMPARE_ENUMS(SOFTMAX);
+COMPARE_ENUMS(SPACE_TO_DEPTH);
+COMPARE_ENUMS(SVDF);
+COMPARE_ENUMS(TANH);
+COMPARE_ENUMS(BATCH_TO_SPACE_ND);
+COMPARE_ENUMS(DIV);
+COMPARE_ENUMS(MEAN);
+COMPARE_ENUMS(PAD);
+COMPARE_ENUMS(SPACE_TO_BATCH_ND);
+COMPARE_ENUMS(SQUEEZE);
+COMPARE_ENUMS(STRIDED_SLICE);
+COMPARE_ENUMS(SUB);
+COMPARE_ENUMS(TRANSPOSE);
+COMPARE_ENUMS(OEM_OPERATION);
+
+#undef COMPARE_ENUMS
+
+#define COMPARE_ENUMS(symbol) COMPARE_ENUMS_FULL(symbol, ExecutionPreference)
+
+COMPARE_ENUMS(LOW_POWER);
+COMPARE_ENUMS(FAST_SINGLE_ANSWER);
+COMPARE_ENUMS(SUSTAINED_SPEED);
+
+#undef COMPARE_ENUMS
+
+#undef COMPARE_ENUMS_FULL
+
+}  // anonymous namespace
diff --git a/neuralnetworks/1.1/utils/src/Conversions.cpp b/neuralnetworks/1.1/utils/src/Conversions.cpp
new file mode 100644
index 0000000..7fee16b
--- /dev/null
+++ b/neuralnetworks/1.1/utils/src/Conversions.cpp
@@ -0,0 +1,209 @@
+/*
+ * 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.
+ */
+
+#include "Conversions.h"
+
+#include <android-base/logging.h>
+#include <android/hardware/neuralnetworks/1.0/types.h>
+#include <android/hardware/neuralnetworks/1.1/types.h>
+#include <nnapi/OperandTypes.h>
+#include <nnapi/OperationTypes.h>
+#include <nnapi/Result.h>
+#include <nnapi/SharedMemory.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/1.0/Conversions.h>
+#include <nnapi/hal/CommonUtils.h>
+
+#include <algorithm>
+#include <functional>
+#include <iterator>
+#include <type_traits>
+#include <utility>
+
+namespace android::nn {
+namespace {
+
+using hardware::hidl_vec;
+
+template <typename Input>
+using convertOutput = std::decay_t<decltype(convert(std::declval<Input>()).value())>;
+
+template <typename Type>
+Result<std::vector<convertOutput<Type>>> convert(const hidl_vec<Type>& arguments) {
+    std::vector<convertOutput<Type>> canonical;
+    canonical.reserve(arguments.size());
+    for (const auto& argument : arguments) {
+        canonical.push_back(NN_TRY(nn::convert(argument)));
+    }
+    return canonical;
+}
+
+}  // anonymous namespace
+
+Result<OperationType> convert(const hal::V1_1::OperationType& operationType) {
+    return static_cast<OperationType>(operationType);
+}
+
+Result<Capabilities> convert(const hal::V1_1::Capabilities& capabilities) {
+    const auto quantized8Performance = NN_TRY(convert(capabilities.quantized8Performance));
+    const auto float32Performance = NN_TRY(convert(capabilities.float32Performance));
+    const auto relaxedFloat32toFloat16Performance =
+            NN_TRY(convert(capabilities.relaxedFloat32toFloat16Performance));
+
+    auto table = hal::utils::makeQuantized8PerformanceConsistentWithP(float32Performance,
+                                                                      quantized8Performance);
+
+    return Capabilities{
+            .relaxedFloat32toFloat16PerformanceScalar = relaxedFloat32toFloat16Performance,
+            .relaxedFloat32toFloat16PerformanceTensor = relaxedFloat32toFloat16Performance,
+            .operandPerformance = std::move(table),
+    };
+}
+
+Result<Operation> convert(const hal::V1_1::Operation& operation) {
+    return Operation{
+            .type = NN_TRY(convert(operation.type)),
+            .inputs = operation.inputs,
+            .outputs = operation.outputs,
+    };
+}
+
+Result<Model> convert(const hal::V1_1::Model& model) {
+    auto operations = NN_TRY(convert(model.operations));
+
+    // Verify number of consumers.
+    const auto numberOfConsumers =
+            hal::utils::countNumberOfConsumers(model.operands.size(), operations);
+    CHECK(model.operands.size() == numberOfConsumers.size());
+    for (size_t i = 0; i < model.operands.size(); ++i) {
+        if (model.operands[i].numberOfConsumers != numberOfConsumers[i]) {
+            return NN_ERROR() << "Invalid numberOfConsumers for operand " << i << ", expected "
+                              << numberOfConsumers[i] << " but found "
+                              << model.operands[i].numberOfConsumers;
+        }
+    }
+
+    auto main = Model::Subgraph{
+            .operands = NN_TRY(convert(model.operands)),
+            .operations = std::move(operations),
+            .inputIndexes = model.inputIndexes,
+            .outputIndexes = model.outputIndexes,
+    };
+
+    return Model{
+            .main = std::move(main),
+            .operandValues = NN_TRY(convert(model.operandValues)),
+            .pools = NN_TRY(convert(model.pools)),
+            .relaxComputationFloat32toFloat16 = model.relaxComputationFloat32toFloat16,
+    };
+}
+
+Result<ExecutionPreference> convert(const hal::V1_1::ExecutionPreference& executionPreference) {
+    return static_cast<ExecutionPreference>(executionPreference);
+}
+
+}  // namespace android::nn
+
+namespace android::hardware::neuralnetworks::V1_1::utils {
+namespace {
+
+using utils::convert;
+
+nn::Result<V1_0::PerformanceInfo> convert(
+        const nn::Capabilities::PerformanceInfo& performanceInfo) {
+    return V1_0::utils::convert(performanceInfo);
+}
+
+nn::Result<V1_0::Operand> convert(const nn::Operand& operand) {
+    return V1_0::utils::convert(operand);
+}
+
+nn::Result<hidl_vec<uint8_t>> convert(const nn::Model::OperandValues& operandValues) {
+    return V1_0::utils::convert(operandValues);
+}
+
+nn::Result<hidl_memory> convert(const nn::Memory& memory) {
+    return V1_0::utils::convert(memory);
+}
+
+template <typename Input>
+using convertOutput = std::decay_t<decltype(convert(std::declval<Input>()).value())>;
+
+template <typename Type>
+nn::Result<hidl_vec<convertOutput<Type>>> convert(const std::vector<Type>& arguments) {
+    hidl_vec<convertOutput<Type>> halObject(arguments.size());
+    for (size_t i = 0; i < arguments.size(); ++i) {
+        halObject[i] = NN_TRY(convert(arguments[i]));
+    }
+    return halObject;
+}
+
+}  // anonymous namespace
+
+nn::Result<OperationType> convert(const nn::OperationType& operationType) {
+    return static_cast<OperationType>(operationType);
+}
+
+nn::Result<Capabilities> convert(const nn::Capabilities& capabilities) {
+    return Capabilities{
+            .float32Performance = NN_TRY(convert(
+                    capabilities.operandPerformance.lookup(nn::OperandType::TENSOR_FLOAT32))),
+            .quantized8Performance = NN_TRY(convert(
+                    capabilities.operandPerformance.lookup(nn::OperandType::TENSOR_QUANT8_ASYMM))),
+            .relaxedFloat32toFloat16Performance =
+                    NN_TRY(convert(capabilities.relaxedFloat32toFloat16PerformanceTensor)),
+    };
+}
+
+nn::Result<Operation> convert(const nn::Operation& operation) {
+    return Operation{
+            .type = NN_TRY(convert(operation.type)),
+            .inputs = operation.inputs,
+            .outputs = operation.outputs,
+    };
+}
+
+nn::Result<Model> convert(const nn::Model& model) {
+    if (!hal::utils::hasNoPointerData(model)) {
+        return NN_ERROR() << "Mdoel cannot be converted because it contains pointer-based memory";
+    }
+
+    auto operands = NN_TRY(convert(model.main.operands));
+
+    // Update number of consumers.
+    const auto numberOfConsumers =
+            hal::utils::countNumberOfConsumers(operands.size(), model.main.operations);
+    CHECK(operands.size() == numberOfConsumers.size());
+    for (size_t i = 0; i < operands.size(); ++i) {
+        operands[i].numberOfConsumers = numberOfConsumers[i];
+    }
+
+    return Model{
+            .operands = std::move(operands),
+            .operations = NN_TRY(convert(model.main.operations)),
+            .inputIndexes = model.main.inputIndexes,
+            .outputIndexes = model.main.outputIndexes,
+            .operandValues = NN_TRY(convert(model.operandValues)),
+            .pools = NN_TRY(convert(model.pools)),
+            .relaxComputationFloat32toFloat16 = model.relaxComputationFloat32toFloat16,
+    };
+}
+
+nn::Result<ExecutionPreference> convert(const nn::ExecutionPreference& executionPreference) {
+    return static_cast<ExecutionPreference>(executionPreference);
+}
+
+}  // namespace android::hardware::neuralnetworks::V1_1::utils