diff --git a/neuralnetworks/1.2/types.hal b/neuralnetworks/1.2/types.hal
index a1a1bad577..4ab0c24ed8 100644
--- a/neuralnetworks/1.2/types.hal
+++ b/neuralnetworks/1.2/types.hal
@@ -40,7 +40,7 @@ enum OperandType : @1.0::OperandType {
      * scale is a 32 bit floating point with value greater then zero.
      */
     TENSOR_QUANT16_SYMM = 7,
-    /** A tensor of 16 bit floating point values. */
+    /** A tensor of IEEE 754 16 bit floating point values. */
     TENSOR_FLOAT16 = 8,
     /**
      * A tensor of 8 bit boolean values.
@@ -49,16 +49,22 @@ enum OperandType : @1.0::OperandType {
      * represents false; any other value represents true.
      */
     TENSOR_BOOL8 = 9,
+    /** An IEEE 754 16 bit floating point scalar value. */
+    FLOAT16 = 10,
+    /* ADDING A NEW FUNDAMENTAL TYPE REQUIRES UPDATING THE VALUE OF
+     * OperandTypeRange::OPERAND_FUNDAMENTAL_MAX.
+     */
+    /* ADDING A NEW OEM TYPE REQUIRES UPDATING THE VALUE OF
+     * OperandTypeRange::OPERAND_OEM_MAX.
+     */
 };
 
 /**
- * The range of values in the OperandType enum.
- *
- * THE MAX VALUES MUST BE UPDATED WHEN ADDING NEW TYPES to the OperandType enum.
+ * The range of operand values in the OperandType enum.
  */
 enum OperandTypeRange : uint32_t {
     OPERAND_FUNDAMENTAL_MIN = 0,
-    OPERAND_FUNDAMENTAL_MAX = 9,
+    OPERAND_FUNDAMENTAL_MAX = 10,
     OPERAND_OEM_MIN     = 10000,
     OPERAND_OEM_MAX     = 10001,
 };
@@ -122,16 +128,22 @@ enum OperationType : @1.1::OperationType {
     ROTATED_BBOX_TRANSFORM = 87,
     ABS = 88,
     ROI_POOLING = 89,
+    EQUAL = 90,
+    NOT_EQUAL = 91,
+    /* ADDING A NEW FUNDAMENTAL OPERATION REQUIRES UPDATING THE VALUE OF
+     * OperationTypeRange::OPERATION_FUNDAMENTAL_MAX.
+     */
+    /* ADDING A NEW OEM OPERATION REQUIRES UPDATING THE VALUE OF
+     * OperationTypeRange::OPERATION_OEM_MAX.
+     */
 };
 
 /**
  * The range of values in the OperationType enum.
- *
- * THE MAX VALUES MUST BE UPDATED WHEN ADDING NEW TYPES to the OperationType enum.
  */
 enum OperationTypeRange : uint32_t {
     OPERATION_FUNDAMENTAL_MIN = 0,
-    OPERATION_FUNDAMENTAL_MAX = 87,
+    OPERATION_FUNDAMENTAL_MAX = 91,
     OPERATION_OEM_MIN = 10000,
     OPERATION_OEM_MAX = 10000,
 };
diff --git a/neuralnetworks/1.2/vts/functional/ValidateModel.cpp b/neuralnetworks/1.2/vts/functional/ValidateModel.cpp
index 802499287a..8f6d54f7f9 100644
--- a/neuralnetworks/1.2/vts/functional/ValidateModel.cpp
+++ b/neuralnetworks/1.2/vts/functional/ValidateModel.cpp
@@ -151,6 +151,7 @@ static void mutateOperandTypeTest(const sp<IDevice>& device, const Model& model)
 
 static uint32_t getInvalidRank(OperandType type) {
     switch (type) {
+        case OperandType::FLOAT16:
         case OperandType::FLOAT32:
         case OperandType::INT32:
         case OperandType::UINT32:
@@ -182,6 +183,7 @@ static void mutateOperandRankTest(const sp<IDevice>& device, const Model& model)
 
 static float getInvalidScale(OperandType type) {
     switch (type) {
+        case OperandType::FLOAT16:
         case OperandType::FLOAT32:
         case OperandType::INT32:
         case OperandType::UINT32:
@@ -214,6 +216,7 @@ static void mutateOperandScaleTest(const sp<IDevice>& device, const Model& model
 
 static std::vector<int32_t> getInvalidZeroPoints(OperandType type) {
     switch (type) {
+        case OperandType::FLOAT16:
         case OperandType::FLOAT32:
         case OperandType::INT32:
         case OperandType::UINT32:
@@ -257,6 +260,7 @@ static void mutateOperand(Operand* operand, OperandType type) {
     Operand newOperand = *operand;
     newOperand.type = type;
     switch (type) {
+        case OperandType::FLOAT16:
         case OperandType::FLOAT32:
         case OperandType::INT32:
         case OperandType::UINT32:
@@ -300,8 +304,9 @@ static bool mutateOperationOperandTypeSkip(size_t operand, OperandType type, con
     for (const Operation& operation : model.operations) {
         // Skip mutateOperationOperandTypeTest for the following operations.
         // - LSH_PROJECTION's second argument is allowed to have any type.
-        // - ARGMIN and ARGMAX's first argument can be any of TENSOR_(FLOAT32|INT32|QUANT8_ASYMM).
-        // - CAST's argument can be any of TENSOR_(FLOAT32|INT32|QUANT8_ASYMM).
+        // - ARGMIN and ARGMAX's first argument can be any of
+        // TENSOR_(FLOAT16|FLOAT32|INT32|QUANT8_ASYMM).
+        // - CAST's argument can be any of TENSOR_(FLOAT16|FLOAT32|INT32|QUANT8_ASYMM).
         switch (operation.type) {
             case OperationType::LSH_PROJECTION: {
                 if (operand == operation.inputs[1]) {
@@ -311,8 +316,8 @@ static bool mutateOperationOperandTypeSkip(size_t operand, OperandType type, con
             case OperationType::CAST:
             case OperationType::ARGMAX:
             case OperationType::ARGMIN: {
-                if (type == OperandType::TENSOR_FLOAT32 || type == OperandType::TENSOR_INT32 ||
-                    type == OperandType::TENSOR_QUANT8_ASYMM) {
+                if (type == OperandType::TENSOR_FLOAT16 || type == OperandType::TENSOR_FLOAT32 ||
+                    type == OperandType::TENSOR_INT32 || type == OperandType::TENSOR_QUANT8_ASYMM) {
                     return true;
                 }
             } break;