diff --git a/tensorflow/python/keras/saving/save.py b/tensorflow/python/keras/saving/save.py
index 4be3aa0bbda..a64df37aeca 100644
--- a/tensorflow/python/keras/saving/save.py
+++ b/tensorflow/python/keras/saving/save.py
@@ -19,6 +19,7 @@ from __future__ import division
 from __future__ import print_function
 
 import os
+import sys
 
 import six
 
@@ -30,6 +31,8 @@ from tensorflow.python.saved_model import loader_impl
 from tensorflow.python.util.tf_export import keras_export
 
 # pylint: disable=g-import-not-at-top
+if sys.version >= '3.4':
+  import pathlib
 try:
   import h5py
 except ImportError:
@@ -73,7 +76,7 @@ def save_model(model,
   Arguments:
       model: Keras model instance to be saved.
       filepath: One of the following:
-        - String, path where to save the model
+        - String or `pathlib.Path` object, path where to save the model
         - `h5py.File` object where to save the model
       overwrite: Whether we should overwrite any existing model at the target
         location, or instead ask the user with a manual prompt.
@@ -95,6 +98,9 @@ def save_model(model,
   default_format = 'tf' if tf2.enabled() else 'h5'
   save_format = save_format or default_format
 
+  if sys.version >= '3.4' and isinstance(filepath, pathlib.Path):
+    filepath = str(filepath)
+
   if (save_format == 'h5' or
       (h5py is not None and isinstance(filepath, h5py.File)) or
       os.path.splitext(filepath)[1] in _HDF5_EXTENSIONS):
@@ -121,7 +127,7 @@ def load_model(filepath, custom_objects=None, compile=True):  # pylint: disable=
 
   Arguments:
       filepath: One of the following:
-          - String, path to the saved model
+          - String or `pathlib.Path` object, path to the saved model
           - `h5py.File` object from which to load the model
       custom_objects: Optional dictionary mapping names
           (strings) to custom classes or functions to be
@@ -145,6 +151,8 @@ def load_model(filepath, custom_objects=None, compile=True):  # pylint: disable=
       isinstance(filepath, h5py.File) or h5py.is_hdf5(filepath))):
     return hdf5_format.load_model_from_hdf5(filepath, custom_objects, compile)
 
+  if sys.version >= '3.4' and isinstance(filepath, pathlib.Path):
+    filepath = str(filepath)
   if isinstance(filepath, six.string_types):
     loader_impl.parse_saved_model(filepath)
     return saved_model_load.load(filepath, compile)
diff --git a/tensorflow/python/keras/saving/save_test.py b/tensorflow/python/keras/saving/save_test.py
index 9f9edf50176..f5fe8041857 100644
--- a/tensorflow/python/keras/saving/save_test.py
+++ b/tensorflow/python/keras/saving/save_test.py
@@ -19,6 +19,7 @@ from __future__ import division
 from __future__ import print_function
 
 import os
+import sys
 
 import numpy as np
 
@@ -34,6 +35,8 @@ from tensorflow.python.ops import lookup_ops
 from tensorflow.python.platform import test
 from tensorflow.python.saved_model import loader_impl
 
+if sys.version >= '3.4':
+  import pathlib  # pylint:disable=g-import-not-at-top
 try:
   import h5py  # pylint:disable=g-import-not-at-top
 except ImportError:
@@ -83,6 +86,19 @@ class TestSaveModel(test.TestCase):
     save.save_model(self.subclassed_model, path, save_format='tf')
     self.assert_saved_model(path)
 
+  @test_util.run_v2_only
+  def test_save_load_tf_string(self):
+    path = os.path.join(self.get_temp_dir(), 'model')
+    save.save_model(self.model, path, save_format='tf')
+    save.load_model(path)
+
+  @test_util.run_v2_only
+  def test_save_load_tf_pathlib(self):
+    if sys.version >= '3.4':
+      path = pathlib.Path(self.get_temp_dir()) / 'model'
+      save.save_model(self.model, path, save_format='tf')
+      save.load_model(path)
+
   @test_util.run_in_graph_and_eager_modes
   def test_saving_with_dense_features(self):
     cols = [