diff --git a/deepwalk/__main__.py b/deepwalk/__main__.py
index c331aef..13c3a56 100644
--- a/deepwalk/__main__.py
+++ b/deepwalk/__main__.py
@@ -88,7 +88,7 @@ def process(args):
                      size=args.representation_size,
                      window=args.window_size, min_count=0, workers=args.workers)
 
-  model.save_word2vec_format(args.output)
+  model.save_word2vec_format(args.output, binary=args.binary)
 
 
 def main():
@@ -143,6 +143,9 @@ def main():
   parser.add_argument('--workers', default=1, type=int,
                       help='Number of parallel processes.')
 
+  parser.add_argument('--binary', action='store_true',
+                      help='Save the resulting vectors in binary moded; default is False (off)')
+
 
   args = parser.parse_args()
   numeric_level = getattr(logging, args.log.upper(), None)
diff --git a/deepwalk/graph.py b/deepwalk/graph.py
index ef1f2d7..29fefbb 100644
--- a/deepwalk/graph.py
+++ b/deepwalk/graph.py
@@ -18,6 +18,7 @@
 from itertools import product,permutations
 from scipy.io import loadmat
 from scipy.sparse import issparse
+from gensim.utils import smart_open
 
 from concurrent.futures import ProcessPoolExecutor
 
@@ -33,7 +34,7 @@
 LOGFORMAT = "%(asctime).19s %(levelname)s %(filename)s: %(lineno)s %(message)s"
 
 class Graph(defaultdict):
-  """Efficient basic implementation of nx `Graph' – Undirected graphs with self loops"""  
+  """Efficient basic implementation of nx `Graph' – Undirected graphs with self loops"""
   def __init__(self):
     super(Graph, self).__init__(list)
 
@@ -45,22 +46,22 @@ def adjacency_iter(self):
 
   def subgraph(self, nodes={}):
     subgraph = Graph()
-    
+
     for n in nodes:
       if n in self:
         subgraph[n] = [x for x in self[n] if x in nodes]
-        
+
     return subgraph
 
   def make_undirected(self):
-  
+
     t0 = time()
 
     for v in self.keys():
       for other in self[v]:
         if v != other:
           self[other].append(v)
-    
+
     t1 = time()
     logger.info('make_directed: added missing edges {}s'.format(t1-t0))
 
@@ -71,7 +72,7 @@ def make_consistent(self):
     t0 = time()
     for k in iterkeys(self):
       self[k] = list(sorted(set(self[k])))
-    
+
     t1 = time()
     logger.info('make_consistent: made consistent in {}s'.format(t1-t0))
 
@@ -85,10 +86,10 @@ def remove_self_loops(self):
     t0 = time()
 
     for x in self:
-      if x in self[x]: 
+      if x in self[x]:
         self[x].remove(x)
         removed += 1
-    
+
     t1 = time()
 
     logger.info('remove_self_loops: removed {} loops in {}s'.format(removed, (t1-t0)))
@@ -99,7 +100,7 @@ def check_self_loops(self):
       for y in self[x]:
         if x == y:
           return True
-    
+
     return False
 
   def has_edge(self, v1, v2):
@@ -115,7 +116,7 @@ def degree(self, nodes=None):
 
   def order(self):
     "Returns the number of nodes in the graph"
-    return len(self)    
+    return len(self)
 
   def number_of_edges(self):
     "Returns the number of nodes in the graph"
@@ -157,12 +158,12 @@ def build_deepwalk_corpus(G, num_paths, path_length, alpha=0,
   walks = []
 
   nodes = list(G.nodes())
-  
+
   for cnt in range(num_paths):
     rand.shuffle(nodes)
     for node in nodes:
       walks.append(G.random_walk(path_length, rand=rand, alpha=alpha, start=node))
-  
+
   return walks
 
 def build_deepwalk_corpus_iter(G, num_paths, path_length, alpha=0,
@@ -194,7 +195,7 @@ def parse_adjacencylist(f):
       row = [introw[0]]
       row.extend(set(sorted(introw[1:])))
       adjlist.extend([row])
-  
+
   return adjlist
 
 def parse_adjacencylist_unchecked(f):
@@ -202,7 +203,7 @@ def parse_adjacencylist_unchecked(f):
   for l in f:
     if l and l[0] != "#":
       adjlist.extend([[int(x) for x in l.strip().split()]])
-  
+
   return adjlist
 
 def load_adjacencylist(file_, undirected=False, chunksize=10000, unchecked=True):
@@ -218,13 +219,13 @@ def load_adjacencylist(file_, undirected=False, chunksize=10000, unchecked=True)
 
   t0 = time()
 
-  with open(file_) as f:
+  with smart_open(file_) as f:
     with ProcessPoolExecutor(max_workers=cpu_count()) as executor:
-      total = 0 
+      total = 0
       for idx, adj_chunk in enumerate(executor.map(parse_func, grouper(int(chunksize), f))):
           adjlist.extend(adj_chunk)
           total += len(adj_chunk)
-  
+
   t1 = time()
 
   logger.info('Parsed {} edges with {} chunks in {}s'.format(total, idx, t1-t0))
@@ -241,12 +242,12 @@ def load_adjacencylist(file_, undirected=False, chunksize=10000, unchecked=True)
     t1 = time()
     logger.info('Made graph undirected in {}s'.format(t1-t0))
 
-  return G 
+  return G
 
 
 def load_edgelist(file_, undirected=True):
   G = Graph()
-  with open(file_) as f:
+  with smart_open(file_) as f:
     for l in f:
       x, y = l.strip().split()[:2]
       x = int(x)
@@ -254,7 +255,7 @@ def load_edgelist(file_, undirected=True):
       G[x].append(y)
       if undirected:
         G[y].append(x)
-  
+
   G.make_consistent()
   return G
 
@@ -298,7 +299,7 @@ def from_numpy(x, undirected=True):
 
 def from_adjlist(adjlist):
     G = Graph()
-    
+
     for row in adjlist:
         node = row[0]
         neighbors = row[1:]
@@ -309,7 +310,7 @@ def from_adjlist(adjlist):
 
 def from_adjlist_unchecked(adjlist):
     G = Graph()
-    
+
     for row in adjlist:
         node = row[0]
         neighbors = row[1:]