diff --git a/current.txt b/current.txt
index 94c845e..a948685 100644
--- a/current.txt
+++ b/current.txt
@@ -655,7 +655,7 @@
 4167dc3ad35e9cd0d2057d4868c7675ae2c3c9d05bbd614c1f5dccfa5fd68797 android.hardware.neuralnetworks@1.3::IExecutionCallback
 7d23020248194abbee8091cc624f39a5a6d7ccba338b172d5d2d3df0cceffbee android.hardware.neuralnetworks@1.3::IPreparedModel
 0439a1fbbec7f16e5e4c653d85ac685d51bfafbae15b8f8cca530acdd7d6a8ce android.hardware.neuralnetworks@1.3::IPreparedModelCallback
-26c643aedf4e28b8d82e517d9cd70601b37f881e1ea94f09808d9e233517e400 android.hardware.neuralnetworks@1.3::types
+5f1a4e0c29fc686ed476f9f04eed35e4405d21288cb2746b978d6891de5cc37d android.hardware.neuralnetworks@1.3::types
 3e01d4446cd69fd1c48f8572efd97487bc179564b32bd795800b97bbe10be37b android.hardware.wifi@1.4::IWifi
 c67aaf26a7a40d14ea61e70e20afacbd0bb906df1704d585ac8599fbb69dd44b android.hardware.wifi.hostapd@1.2::IHostapd
 11f6448d15336361180391c8ebcdfd2d7cf77b3782d577e594d583aadc9c2877 android.hardware.wifi.hostapd@1.2::types
diff --git a/neuralnetworks/1.3/types.hal b/neuralnetworks/1.3/types.hal
index 6a852d1..abc33e7 100644
--- a/neuralnetworks/1.3/types.hal
+++ b/neuralnetworks/1.3/types.hal
@@ -5037,6 +5037,56 @@
     HARD_SWISH = 99,
 
     /**
+     * Creates a tensor filled with a scalar value.
+     *
+     * Supported output tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_INT32}
+     *
+     * Inputs:
+     * * 0: A 1-D tensor, specifying the desired output tensor shape.
+     * * 1: A scalar, specifying the value to fill the output tensors with.
+     *      For output tensor of {@link OperandType::TENSOR_FLOAT16},
+     *      the scalar must be of {@link OperandType::FLOAT16}.
+     *      For output tensor of {@link OperandType::TENSOR_FLOAT32},
+     *      the scalar must be of {@link OperandType::FLOAT32}.
+     *      For output tensor of {@link OperandType::TENSOR_INT32},
+     *      the scalar must be of {@link OperandType::INT32}.
+     *
+     * Outputs:
+     * * 0: The output tensor.
+     */
+    FILL = 100,
+
+    /**
+     * Returns the rank of a tensor.
+     *
+     * The rank of a tensor is the number of dimensions in it. Also known as
+     * "order", "degree", "ndims".
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_INT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT16_SYMM}
+     * * {@link OperandType::TENSOR_BOOL8}
+     * * {@link OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL}
+     * * {@link OperandType::TENSOR_QUANT16_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_SYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED}
+     *
+     * Inputs:
+     * * 0: The input tensor.
+     *
+     * Outputs:
+     * * 0: A scalar of {@link OperandType::INT32}, specifying the rank
+     *      of the input tensor.
+     */
+    RANK = 101,
+
+    /**
      * DEPRECATED. Since NNAPI 1.2, extensions are the preferred alternative to
      * OEM operation and data types.
      *
@@ -5058,7 +5108,7 @@
 enum OperationTypeRange : uint32_t {
     BASE_MIN        = 0,
     FUNDAMENTAL_MIN = 0,
-    FUNDAMENTAL_MAX = 99,
+    FUNDAMENTAL_MAX = 101,
     OEM_MIN         = 10000,
     OEM_MAX         = 10000,
     BASE_MAX        = 0xFFFF,
diff --git a/neuralnetworks/1.3/vts/functional/GeneratedTestHarness.cpp b/neuralnetworks/1.3/vts/functional/GeneratedTestHarness.cpp
index a2c0c4e..cba1f77 100644
--- a/neuralnetworks/1.3/vts/functional/GeneratedTestHarness.cpp
+++ b/neuralnetworks/1.3/vts/functional/GeneratedTestHarness.cpp
@@ -793,8 +793,9 @@
 INSTANTIATE_GENERATED_TEST(GeneratedTest,
                            [](const TestModel& testModel) { return !testModel.expectFailure; });
 
-INSTANTIATE_GENERATED_TEST(DynamicOutputShapeTest,
-                           [](const TestModel& testModel) { return !testModel.expectFailure; });
+INSTANTIATE_GENERATED_TEST(DynamicOutputShapeTest, [](const TestModel& testModel) {
+    return !testModel.expectFailure && !testModel.hasScalarOutputs();
+});
 
 INSTANTIATE_GENERATED_TEST(MemoryDomainTest,
                            [](const TestModel& testModel) { return !testModel.expectFailure; });
diff --git a/neuralnetworks/1.3/vts/functional/ValidateModel.cpp b/neuralnetworks/1.3/vts/functional/ValidateModel.cpp
index a211428..1245432 100644
--- a/neuralnetworks/1.3/vts/functional/ValidateModel.cpp
+++ b/neuralnetworks/1.3/vts/functional/ValidateModel.cpp
@@ -337,6 +337,7 @@
         // - TRANSPOSE_CONV_2D filter type (arg 1) can be QUANT8_ASYMM or QUANT8_SYMM_PER_CHANNEL
         // - AXIS_ALIGNED_BBOX_TRANSFORM bounding boxes (arg 1) can be of
         //     TENSOR_QUANT8_ASYMM or TENSOR_QUANT8_ASYMM_SIGNED.
+        // - RANK's input can have any TENSOR_* type.
         switch (operation.type) {
             case OperationType::LSH_PROJECTION: {
                 if (operand == operation.inputs[1]) {
@@ -399,6 +400,20 @@
                     return true;
                 }
             } break;
+            case OperationType::RANK: {
+                if (operand == operation.inputs[0] &&
+                    (type == OperandType::TENSOR_FLOAT16 || type == OperandType::TENSOR_FLOAT32 ||
+                     type == OperandType::TENSOR_INT32 ||
+                     type == OperandType::TENSOR_QUANT8_ASYMM ||
+                     type == OperandType::TENSOR_QUANT16_SYMM ||
+                     type == OperandType::TENSOR_BOOL8 ||
+                     type == OperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL ||
+                     type == OperandType::TENSOR_QUANT16_ASYMM ||
+                     type == OperandType::TENSOR_QUANT8_SYMM ||
+                     type == OperandType::TENSOR_QUANT8_ASYMM_SIGNED)) {
+                    return true;
+                }
+            } break;
             default:
                 break;
         }