diff --git a/nnvm/python/nnvm/frontend/keras.py b/nnvm/python/nnvm/frontend/keras.py
index a4d43cd43709..0d51487c355d 100644
--- a/nnvm/python/nnvm/frontend/keras.py
+++ b/nnvm/python/nnvm/frontend/keras.py
@@ -40,7 +40,7 @@ def _convert_activation(insym, keras_layer, _):
         return _sym.__add_scalar__(_sym.__mul_scalar__(insym, \
             scalar=alpha), scalar=beta)
     elif act_type == 'softmax':
-        return _sym.softmax(insym)
+        return _sym.softmax(insym, axis=1)
     elif act_type == 'sigmoid':
         return _sym.sigmoid(insym)
     elif act_type == 'tanh':
diff --git a/nnvm/tests/python/frontend/keras/test_forward.py b/nnvm/tests/python/frontend/keras/test_forward.py
index 58a3d8c12ff6..0147a3e2c654 100644
--- a/nnvm/tests/python/frontend/keras/test_forward.py
+++ b/nnvm/tests/python/frontend/keras/test_forward.py
@@ -59,6 +59,15 @@ def test_forward_elemwise_add():
     verify_keras_frontend(keras_model)
 
 
+def test_forward_softmax():
+    data = keras.layers.Input(shape=(32,32,3))
+    x = keras.layers.Activation('softmax')(data)
+    x = keras.layers.Concatenate()([x, x])
+    x = keras.layers.GlobalMaxPooling2D()(x)
+    keras_model = keras.models.Model(data, x)
+    verify_keras_frontend(keras_model)
+
+
 def test_forward_softrelu():
     data = keras.layers.Input(shape=(32,32,3))
     x = keras.layers.Activation('softplus')(data)
@@ -145,6 +154,7 @@ def test_forward_resnet50():
 
 if __name__ == '__main__':
     test_forward_elemwise_add()
+    test_forward_softmax()
     test_forward_softrelu()
     test_forward_leaky_relu()
     test_forward_dense()