diff --git a/tensorflow/lite/python/tflite_convert.py b/tensorflow/lite/python/tflite_convert.py
index d0dd7313df3..c7504a3a638 100644
--- a/tensorflow/lite/python/tflite_convert.py
+++ b/tensorflow/lite/python/tflite_convert.py
@@ -65,6 +65,8 @@ def _parse_inference_type(value, flag):
     return lite_constants.FLOAT
   if value == "QUANTIZED_UINT8":
     return lite_constants.QUANTIZED_UINT8
+  if value == "INT8":
+    return lite_constants.INT8
   raise ValueError("Unsupported value for --{0}. Only FLOAT and "
                    "QUANTIZED_UINT8 are supported.".format(flag))
 
@@ -352,12 +354,12 @@ def _get_tf1_flags(parser):
   parser.add_argument(
       "--inference_type",
       type=str.upper,
-      choices=["FLOAT", "QUANTIZED_UINT8"],
+      choices=["FLOAT", "QUANTIZED_UINT8", "INT8"],
       help="Target data type of real-number arrays in the output file.")
   parser.add_argument(
       "--inference_input_type",
       type=str.upper,
-      choices=["FLOAT", "QUANTIZED_UINT8"],
+      choices=["FLOAT", "QUANTIZED_UINT8", "INT8"],
       help=("Target data type of real-number input arrays. Allows for a "
             "different type for input arrays in the case of quantization."))
 
diff --git a/tensorflow/lite/python/tflite_convert_test.py b/tensorflow/lite/python/tflite_convert_test.py
index 1e80907edbd..d6a35ba9248 100644
--- a/tensorflow/lite/python/tflite_convert_test.py
+++ b/tensorflow/lite/python/tflite_convert_test.py
@@ -98,8 +98,8 @@ class TfLiteConvertV1Test(TestModels):
     sess.close()
 
     flags_str = ('--graph_def_file={0} --input_arrays={1} '
-                 '--output_arrays={2}'.format(graph_def_file,
-                                              'Placeholder', 'add'))
+                 '--output_arrays={2}'.format(graph_def_file, 'Placeholder',
+                                              'add'))
     self._run(flags_str, should_succeed=True)
     os.remove(graph_def_file)
 
@@ -137,8 +137,31 @@ class TfLiteConvertV1Test(TestModels):
     sess.close()
 
     flags_str = ('--graph_def_file={0} --input_arrays={1} '
-                 '--output_arrays={2}'.format(graph_def_file,
-                                              'random', 'add'))
+                 '--output_arrays={2}'.format(graph_def_file, 'random', 'add'))
+    self._run(flags_str, should_succeed=True)
+    os.remove(graph_def_file)
+
+  def testQATFrozenGraphDefInt8(self):
+    with ops.Graph().as_default():
+      in_tensor_1 = array_ops.placeholder(
+          shape=[1, 16, 16, 3], dtype=dtypes.float32, name='inputA')
+      in_tensor_2 = array_ops.placeholder(
+          shape=[1, 16, 16, 3], dtype=dtypes.float32, name='inputB')
+      _ = array_ops.fake_quant_with_min_max_args(
+          in_tensor_1 + in_tensor_2, min=0., max=1., name='output',
+          num_bits=16)  # INT8 inference type works for 16 bits fake quant.
+      sess = session.Session()
+
+    # Write graph to file.
+    graph_def_file = self._getFilepath('model.pb')
+    write_graph(sess.graph_def, '', graph_def_file, False)
+    sess.close()
+
+    flags_str = ('--inference_type=INT8 --std_dev_values=128,128 '
+                 '--mean_values=128,128 '
+                 '--graph_def_file={0} --input_arrays={1},{2} '
+                 '--output_arrays={3}'.format(graph_def_file, 'inputA',
+                                              'inputB', 'output'))
     self._run(flags_str, should_succeed=True)
     os.remove(graph_def_file)
 
@@ -166,8 +189,8 @@ class TfLiteConvertV1Test(TestModels):
   def testKerasFileMLIR(self):
     keras_file = self._getKerasModelFile()
 
-    flags_str = ('--keras_model_file={} --experimental_new_converter'
-                 .format(keras_file))
+    flags_str = (
+        '--keras_model_file={} --experimental_new_converter'.format(keras_file))
     self._run(flags_str, should_succeed=True)
     os.remove(keras_file)
 
@@ -299,8 +322,8 @@ class TfLiteConvertV2Test(TestModels):
   def testKerasFileMLIR(self):
     keras_file = self._getKerasModelFile()
 
-    flags_str = ('--keras_model_file={} --experimental_new_converter'
-                 .format(keras_file))
+    flags_str = (
+        '--keras_model_file={} --experimental_new_converter'.format(keras_file))
     self._run(flags_str, should_succeed=True)
     os.remove(keras_file)