diff --git a/neuralnetworks/1.1/IDevice.hal b/neuralnetworks/1.1/IDevice.hal
index 9d3fc312a6..ca225554d5 100644
--- a/neuralnetworks/1.1/IDevice.hal
+++ b/neuralnetworks/1.1/IDevice.hal
@@ -24,6 +24,20 @@ import @1.0::IPreparedModelCallback;
  * This interface represents a device driver.
  */
 interface IDevice extends @1.0::IDevice {
+    /**
+     * Gets the capabilities of a driver.
+     *
+     * Note that @1.1::Capabilities provides performance information
+     * on relaxed calculations, whereas @1.0::Capabilities does not.
+     *
+     * @return status Error status of the call, must be:
+     *                - NONE if successful
+     *                - DEVICE_UNAVAILABLE if driver is offline or busy
+     *                - GENERAL_FAILURE if there is an unspecified error
+     * @return capabilities Capabilities of the driver.
+     */
+    getCapabilities_1_1() generates (ErrorStatus status, Capabilities capabilities);
+
     /**
      * Gets the supported operations in a model.
      *
diff --git a/neuralnetworks/1.1/types.hal b/neuralnetworks/1.1/types.hal
index fae5dd0caa..1d470d636f 100644
--- a/neuralnetworks/1.1/types.hal
+++ b/neuralnetworks/1.1/types.hal
@@ -18,6 +18,7 @@ package android.hardware.neuralnetworks@1.1;
 
 import @1.0::Operand;
 import @1.0::OperationType;
+import @1.0::PerformanceInfo;
 
 /**
  * Operation types.
@@ -258,6 +259,28 @@ enum OperationType : @1.0::OperationType {
     TRANSPOSE = 37,
 };
 
+/**
+ * The capabilities of a driver.
+ */
+struct Capabilities {
+    /**
+     * Driver performance when operating on float32 data.
+     */
+    PerformanceInfo float32Performance;
+
+    /**
+     * Driver performance when operating on asymmetric 8-bit quantized data.
+     */
+    PerformanceInfo quantized8Performance;
+
+    /**
+     * Driver performance when operating on float32 data but performing
+     * calculations with range and/or precision as low as that of the IEEE
+     * 754 16-bit floating-point format.
+     */
+    PerformanceInfo relaxedFloat32toFloat16Performance;
+};
+
 /**
  * Describes one operation of the model's graph.
  */
diff --git a/neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworksV1_1BasicTest.cpp b/neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworksV1_1BasicTest.cpp
index 51eff2a019..d2e99a7064 100644
--- a/neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworksV1_1BasicTest.cpp
+++ b/neuralnetworks/1.1/vts/functional/VtsHalNeuralnetworksV1_1BasicTest.cpp
@@ -29,7 +29,6 @@
 #include <hidlmemory/mapping.h>
 
 using ::android::hardware::neuralnetworks::V1_0::IPreparedModel;
-using ::android::hardware::neuralnetworks::V1_0::Capabilities;
 using ::android::hardware::neuralnetworks::V1_0::DeviceStatus;
 using ::android::hardware::neuralnetworks::V1_0::ErrorStatus;
 using ::android::hardware::neuralnetworks::V1_0::FusedActivationFunc;
@@ -37,6 +36,7 @@ using ::android::hardware::neuralnetworks::V1_0::Operand;
 using ::android::hardware::neuralnetworks::V1_0::OperandLifeTime;
 using ::android::hardware::neuralnetworks::V1_0::OperandType;
 using ::android::hardware::neuralnetworks::V1_0::Request;
+using ::android::hardware::neuralnetworks::V1_1::Capabilities;
 using ::android::hardware::neuralnetworks::V1_1::IDevice;
 using ::android::hardware::neuralnetworks::V1_1::Model;
 using ::android::hardware::neuralnetworks::V1_1::Operation;
@@ -95,12 +95,14 @@ TEST_F(NeuralnetworksHidlTest, StatusTest) {
 // initialization
 TEST_F(NeuralnetworksHidlTest, GetCapabilitiesTest) {
     Return<void> ret =
-        device->getCapabilities([](ErrorStatus status, const Capabilities& capabilities) {
+        device->getCapabilities_1_1([](ErrorStatus status, const Capabilities& capabilities) {
             EXPECT_EQ(ErrorStatus::NONE, status);
             EXPECT_LT(0.0f, capabilities.float32Performance.execTime);
             EXPECT_LT(0.0f, capabilities.float32Performance.powerUsage);
             EXPECT_LT(0.0f, capabilities.quantized8Performance.execTime);
             EXPECT_LT(0.0f, capabilities.quantized8Performance.powerUsage);
+            EXPECT_LT(0.0f, capabilities.relaxedFloat32toFloat16Performance.execTime);
+            EXPECT_LT(0.0f, capabilities.relaxedFloat32toFloat16Performance.powerUsage);
         });
     EXPECT_TRUE(ret.isOk());
 }