diff --git a/current.txt b/current.txt
index 60ee345..ffd944a 100644
--- a/current.txt
+++ b/current.txt
@@ -621,13 +621,16 @@
 9e59fffceed0dd72a9799e04505db5f777bbbea1af0695ba4107ef6d967c6fda android.hardware.neuralnetworks@1.3::IDevice
 258825966435b3ed08832055bb736d81516013e405f161d9ccde9a90cfcdde83 android.hardware.neuralnetworks@1.3::IPreparedModel
 94e803236398bed1febb11cc21051bc42ec003700139b099d6c479e02a7ca3c3 android.hardware.neuralnetworks@1.3::IPreparedModelCallback
-35668befe89fc7f84d58fc1dab7dd3e4d6067c7eeccbae154fe36cd964dfaef7 android.hardware.neuralnetworks@1.3::types
+618a628f8c94d6f6e4cb401b69fa50ccb8b82191ea434e3a071252289b4f312c android.hardware.neuralnetworks@1.3::types
 3e01d4446cd69fd1c48f8572efd97487bc179564b32bd795800b97bbe10be37b android.hardware.wifi@1.4::IWifi
 a64467bae843569f0d465c5be7f0c7a5b987985b55a3ef4794dd5afc68538650 android.hardware.wifi.supplicant@1.3::ISupplicant
 44445b8a03d7b9e68b2fbd954672c18a8fce9e32851b0692f4f4ab3407f86ecb android.hardware.wifi.supplicant@1.3::ISupplicantStaIface
 619fc9839ec6e369cfa9b28e3e9412e6885720ff8f9b5750c1b6ffb905120391 android.hardware.wifi.supplicant@1.3::ISupplicantStaIfaceCallback
 c9273429fcf98d797d3bb07fdba6f1be95bf960f9255cde169fd1ca4db85f856 android.hardware.wifi.supplicant@1.3::ISupplicantStaNetwork
 9b0a3ab6f4f74b971ed094426d8a443e29b512ff03e1ab50c07156396cdb2483 android.hardware.wifi.supplicant@1.3::types
+##
+# BEGIN Radio HAL Merge Conflict Avoidance Buffer - STOPSHIP if present
+##
 2c0587a1e83facba604949c31163486f21eb5b47a29c8f29119a47d3bd052103 android.hardware.radio@1.5::types
 b5cfa87882b416105fe01e8a40a856d36c93d64f1103d77e12b1281cea13b0bd android.hardware.radio@1.5::IRadio
 bc59237dbd93949238081f762710552e76670cb648c0e198138551460ac54b1e android.hardware.radio@1.5::IRadioIndication
@@ -636,3 +639,6 @@
 b27ab0cd40b0b078cdcd024bfe1061c4c4c065f3519eeb9347fa359a3268a5ae android.hardware.radio.config@1.3::IRadioConfig
 742360c775313438b0f82256eac62fb5bbc76a6ae6f388573f3aa142fb2c1eea android.hardware.radio.config@1.3::IRadioConfigIndication
 7683fed9d253956071f18b152e6be657719536f98d9b534433d5e411bcde5061 android.hardware.radio.config@1.3::IRadioConfigResponse
+##
+# END Radio HAL Merge Conflict Avoidance Buffer - STOPSHIP if present
+##
diff --git a/neuralnetworks/1.3/types.hal b/neuralnetworks/1.3/types.hal
index b70bd1b..74c259c 100644
--- a/neuralnetworks/1.3/types.hal
+++ b/neuralnetworks/1.3/types.hal
@@ -4747,6 +4747,135 @@
     RESIZE_NEAREST_NEIGHBOR = @1.2::OperationType:RESIZE_NEAREST_NEIGHBOR,
 
     /**
+     * Quantized version of {@link OperationType:LSTM}.
+     *
+     * The input and the output use asymmetric quantized types, while the rest
+     * use symmetric ones.
+     *
+     * Inputs:
+     * * 0: The input to the LSTM cell.
+     *      Type: {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED}
+     *      Shape: [batchSize, inputSize]
+     * * 1: The input-to-input weights. Optional.
+     *      Type: {@link OperandType::TENSOR_QUANT8_SYMM}
+     *      Shape: [numUnits, inputSize]
+     * * 2: The input-to-forget weights.
+     *      Type: {@link OperandType::TENSOR_QUANT8_SYMM}
+     *      Shape: [numUnits, inputSize]
+     * * 3: The input-to-cell weights.
+     *      Type: {@link OperandType::TENSOR_QUANT8_SYMM}
+     *      Shape: [numUnits, inputSize]
+     * * 4: The input-to-output weights.
+     *      Type: {@link OperandType::TENSOR_QUANT8_SYMM}
+     *      Shape: [numUnits, inputSize]
+     * * 5: The recurrent-to-input weights. Optional.
+     *      Type: {@link OperandType::TENSOR_QUANT8_SYMM}
+     *      Shape: [numUnits, outputSize]
+     * * 6: The recurrent-to-forget weights.
+     *      Type: {@link OperandType::TENSOR_QUANT8_SYMM}
+     *      Shape: [numUnits, outputSize]
+     * * 7: The recurrent-to-cell weights.
+     *      Type: {@link OperandType::TENSOR_QUANT8_SYMM}
+     *      Shape: [numUnits, outputSize]
+     * * 8: The recurrent-to-output weights.
+     *      Type: {@link OperandType::TENSOR_QUANT8_SYMM}
+     *      Shape: [numUnits, outputSize]
+     * * 9: The cell-to-input weights (for peephole). Optional.
+     *      Type: {@link OperandType::TENSOR_QUANT16_SYMM}
+     *      Shape: [numUnits]
+     * * 10: The cell-to-forget weights (for peephole). Optional.
+     *       Type: {@link OperandType::TENSOR_QUANT16_SYMM}
+     *       Shape: [numUnits]
+     * * 11: The cell-to-output weights (for peephole). Optional.
+     *       Type: {@link OperandType::TENSOR_QUANT16_SYMM}
+     *       Shape: [numUnits]
+     * * 12: The input gate bias. Quantized with scale being the
+     *       product of input and weights scales and zeroPoint equal to 0.
+     *       Optional.
+     *       Type: {@link OperandType::TENSOR_INT32}
+     *       Shape: [numUnits]
+     * * 13: The forget gate bias. Quantized with scale being the
+     *       product of input and weights scales and zeroPoint equal to 0.
+     *       Type: {@link OperandType::TENSOR_INT32}
+     *       Shape: [numUnits]
+     * * 14: The cell bias. Quantized with scale being the
+     *       product of input and weights scales and zeroPoint equal to 0.
+     *       Type: {@link OperandType::TENSOR_INT32}
+     *       Shape: [numUnits]
+     * * 15: The output gate bias. Quantized with scale being the
+     *       product of input and weights scales and zeroPoint equal to 0.
+     *       Type: {@link OperandType::TENSOR_INT32}
+     *       Shape: [numUnits]
+     * * 16: The projection weights. Optional.
+     *       Type: {@link OperandType::TENSOR_QUANT8_SYMM}
+     *       Shape: [outputSize, numUnits]
+     * * 17: The projection bias. Quantized with scale being the
+     *       product of input and weights scales and zeroPoint equal to 0.
+     *       Optional.
+     *       Type: {@link OperandType::TENSOR_INT32}
+     *       Shape: [outputSize]
+     * * 18: The output from the previous time step.
+     *       Type: {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED}
+     *       Shape: [batchSize, outputSize]
+     * * 19: The cell state from the previous time step.
+     *       Type: {@link OperandType::TENSOR_QUANT16_SYMM}
+     *       Shape: [batchSize, numUnits]
+     * * 20: The input layer normalization weights. Used to rescale
+     *       normalized inputs to activation at input gate. Optional.
+     *       Type: {@link OperandType::TENSOR_QUANT16_SYMM}
+     *       Shape: [numUnits]
+     * * 21: The forget layer normalization weights. Used to
+     *       rescale normalized inputs to activation at forget gate. Optional.
+     *       Type: {@link OperandType::TENSOR_QUANT16_SYMM}
+     *       Shape: [numUnits]
+     * * 22: The cell layer normalization weights. Used to rescale
+     *       normalized inputs to activation at cell gate. Optional.
+     *       Type: {@link OperandType::TENSOR_QUANT16_SYMM}
+     *       Shape: [numUnits]
+     * * 23: The output layer normalization weights. Used to
+     *       rescale normalized inputs to activation at output gate. Optional.
+     *       Type: {@link OperandType::TENSOR_QUANT16_SYMM}
+     *       Shape: [numUnits]
+     * * 24: The cell clip. If provided the cell state is clipped
+     *       by this value prior to the cell output activation. Optional.
+     *       Type: {@link OperandType::FLOAT32}.
+     * * 25: The projection clip. If provided and projection is enabled,
+     *       this is used for clipping the projected values. Optional.
+     *       Type: {@link OperandType::FLOAT32}.
+     * * 26: The scale of the intermediate result of matmul,
+     *       i.e. input to layer normalization, at input gate.
+     *       Type: {@link OperandType::FLOAT32}.
+     * * 27: The scale of the intermediate result of matmul,
+     *       i.e. input to layer normalization, at forget gate.
+     *       Type: {@link OperandType::FLOAT32}.
+     * * 28: The scale of the intermediate result of matmul,
+     *       i.e. input to layer normalization, at cell gate.
+     *       Type: {@link OperandType::FLOAT32}.
+     * * 29: The scale of the intermediate result of matmul,
+     *       i.e. input to layer normalization, at output gate.
+     *       Type: {@link OperandType::FLOAT32}.
+     * * 30: The zero point of the hidden state, i.e. input to
+     *       projection.
+     *       Type: {@link OperandType::INT32}.
+     * * 31: The scale of the hidden state, i.e. input to
+     *       projection.
+     *       Type: {@link OperandType::FLOAT32}.
+     *
+     * Outputs:
+     * * 0: The output state (out).
+     *      Type: {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED}
+     *      Shape: [batchSize, outputSize]
+     * * 1: The cell state (out).
+     *      Type: {@link OperandType::TENSOR_QUANT16_SYMM}
+     *      Shape: [batchSize, numUnits]
+     * * 2: The output. This is effectively the same as the current
+     *      "output state (out)" value.
+     *      Type: {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED}
+     *      Shape: [batchSize, outputSize]
+     */
+    QUANTIZED_LSTM = 95,
+
+    /**
      * DEPRECATED. Since NNAPI 1.2, extensions are the preferred alternative to
      * OEM operation and data types.
      *
@@ -4768,7 +4897,7 @@
 enum OperationTypeRange : uint32_t {
     BASE_MIN        = 0,
     FUNDAMENTAL_MIN = 0,
-    FUNDAMENTAL_MAX = 94,
+    FUNDAMENTAL_MAX = 95,
     OEM_MIN         = 10000,
     OEM_MAX         = 10000,
     BASE_MAX        = 0xFFFF,
diff --git a/neuralnetworks/1.3/vts/functional/ValidateModel.cpp b/neuralnetworks/1.3/vts/functional/ValidateModel.cpp
index 14ab897..8395111 100644
--- a/neuralnetworks/1.3/vts/functional/ValidateModel.cpp
+++ b/neuralnetworks/1.3/vts/functional/ValidateModel.cpp
@@ -27,7 +27,6 @@
 using V1_0::ErrorStatus;
 using V1_0::OperandLifeTime;
 using V1_1::ExecutionPreference;
-using V1_2::OperationTypeRange;
 using V1_2::SymmPerChannelQuantParams;
 using HidlToken =
         hidl_array<uint8_t, static_cast<uint32_t>(V1_2::Constant::BYTE_SIZE_OF_CACHE_TOKEN)>;