diff --git a/tensorflow/python/data/benchmarks/BUILD b/tensorflow/python/data/benchmarks/BUILD
index 5b0500eae1970b4f183737d4fc0cd4171dd1ea15..fd0eca9dd7012ce44435dbbf6749121022c7ba29 100644
--- a/tensorflow/python/data/benchmarks/BUILD
+++ b/tensorflow/python/data/benchmarks/BUILD
@@ -48,6 +48,20 @@ py_test(
     ],
 )
 
+py_test(
+    name = "list_files_benchmark",
+    srcs = ["list_files_benchmark.py"],
+    srcs_version = "PY2AND3",
+    deps = [
+        "//tensorflow/python:client_testlib",
+        "//tensorflow/python:errors",
+        "//tensorflow/python:framework_ops",
+        "//tensorflow/python:session",
+        "//tensorflow/python/data/ops:dataset_ops",
+        "//third_party/py/numpy",
+    ],
+)
+
 py_test(
     name = "map_benchmark",
     srcs = ["map_benchmark.py"],
diff --git a/tensorflow/python/data/benchmarks/list_files_benchmark.py b/tensorflow/python/data/benchmarks/list_files_benchmark.py
new file mode 100644
index 0000000000000000000000000000000000000000..0dc21471129d5ca288a68c957e424035fea9dd66
--- /dev/null
+++ b/tensorflow/python/data/benchmarks/list_files_benchmark.py
@@ -0,0 +1,96 @@
+# Copyright 2018 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+"""Benchmarks for `tf.data.Dataset.list_files()`."""
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+from os import path
+from os import makedirs
+import shutil
+import time
+import tempfile
+
+import numpy as np
+
+from tensorflow.python.client import session
+from tensorflow.python.data.ops import dataset_ops
+from tensorflow.python.framework import errors
+from tensorflow.python.framework import ops
+from tensorflow.python.platform import test
+
+
+class ListFilesBenchmark(test.Benchmark):
+  """Benchmarks for `tf.data.Dataset.list_files()`."""
+
+  def benchmarkNestedDirectories(self):
+    tmp_dir = tempfile.mkdtemp()
+    width = 1024
+    depth = 16
+    for i in range(width):
+      for j in range(depth):
+        new_base = path.join(tmp_dir, str(i),
+                             *[str(dir_name) for dir_name in range(j)])
+        makedirs(new_base)
+        child_files = ['a.py', 'b.pyc'] if j < depth - 1 else ['c.txt', 'd.log']
+        for f in child_files:
+          filename = path.join(new_base, f)
+          open(filename, 'w').close()
+    patterns = [
+        path.join(tmp_dir, path.join(*['**'
+                                       for _ in range(depth)]), suffix)
+        for suffix in ['*.txt', '*.log']
+    ]
+    deltas = []
+    iters = 3
+    for _ in range(iters):
+      with ops.Graph().as_default():
+        dataset = dataset_ops.Dataset.list_files(patterns)
+        next_element = dataset.make_one_shot_iterator().get_next()
+        with session.Session() as sess:
+          sub_deltas = []
+          while True:
+            try:
+              start = time.time()
+              sess.run(next_element)
+              end = time.time()
+              sub_deltas.append(end - start)
+            except errors.OutOfRangeError:
+              break
+          deltas.append(sub_deltas)
+    median_deltas = np.median(deltas, axis=0)
+    print('Nested directory size (width*depth): %d*%d Median wall time: '
+          '%fs (read first filename), %fs (read second filename), avg %fs'
+          ' (read %d more filenames)' %
+          (width, depth, median_deltas[0], median_deltas[1],
+           np.average(median_deltas[2:]), len(median_deltas) - 2))
+    self.report_benchmark(
+        iters=iters,
+        wall_time=np.sum(median_deltas),
+        extras={
+            'read first file:':
+                median_deltas[0],
+            'read second file:':
+                median_deltas[1],
+            'avg time for reading %d more filenames:' %
+            (len(median_deltas) - 2):
+                np.average(median_deltas[2:])
+        },
+        name='nested_directory(%d*%d)' % (width, depth))
+    shutil.rmtree(tmp_dir, ignore_errors=True)
+
+
+if __name__ == '__main__':
+  test.main()