diff --git a/doc/source/tune/guides/plot_tune-distributed.rst b/doc/source/tune/guides/plot_tune-distributed.rst
index 1215bc4be..a1f3ad193 100644
--- a/doc/source/tune/guides/plot_tune-distributed.rst
+++ b/doc/source/tune/guides/plot_tune-distributed.rst
@@ -50,7 +50,7 @@ If you used a cluster configuration (starting a cluster with ``ray up`` or ``ray
 
 .. code-block:: bash
 
-    ray submit tune-default.yaml tune_script.py --args="--ray-address=localhost:6379"
+    ray submit tune-default.yaml tune_script.py -- --ray-address=localhost:6379
 
 .. tip::
 
@@ -77,7 +77,7 @@ If you already have a list of nodes, you can follow the local private cluster se
 
 .. code-block:: bash
 
-    ray submit tune-default.yaml tune_script.py --args="--ray-address=localhost:6379"
+    ray submit tune-default.yaml tune_script.py -- --ray-address=localhost:6379
 
 Manual Local Cluster Setup
 ~~~~~~~~~~~~~~~~~~~~~~~~~~
@@ -133,7 +133,7 @@ Ray currently supports AWS and GCP. Follow the instructions below to launch node
 
 .. code-block:: bash
 
-    ray submit tune-default.yaml tune_script.py --start --args="--ray-address=localhost:6379"
+    ray submit tune-default.yaml tune_script.py --start -- --ray-address=localhost:6379
 
 .. image:: /images/tune-upload.png
     :scale: 50%
@@ -221,9 +221,8 @@ Here is an example for running Tune on spot instances. This assumes your AWS cre
 
 .. code-block:: bash
 
-    ray submit tune-default.yaml mnist_pytorch_trainable.py \
-        --args="--ray-address=localhost:6379" \
-        --start
+    ray submit tune-default.yaml mnist_pytorch_trainable.py --start -- --ray-address=localhost:6379
+
 
 4. Optionally for testing on AWS or GCP, you can use the following to kill a random worker node after all the worker nodes are up
 
@@ -237,7 +236,7 @@ To summarize, here are the commands to run:
 
     wget https://raw.githubusercontent.com/ray-project/ray/master/python/ray/tune/examples/mnist_pytorch_trainable.py
     wget https://raw.githubusercontent.com/ray-project/ray/master/python/ray/tune/tune-default.yaml
-    ray submit tune-default.yaml mnist_pytorch_trainable.py --args="--ray-address=localhost:6379" --start
+    ray submit tune-default.yaml mnist_pytorch_trainable.py --start -- --ray-address=localhost:6379
 
     # wait a while until after all nodes have started
     ray kill-random-node tune-default.yaml --hard
@@ -257,12 +256,12 @@ Below are some commonly used commands for submitting experiments. Please see the
 
     # Upload `tune_experiment.py` from your local machine onto the cluster. Then,
     # run `python tune_experiment.py --address=localhost:6379` on the remote machine.
-    $ ray submit CLUSTER.YAML tune_experiment.py --args="--address=localhost:6379"
+    $ ray submit CLUSTER.YAML tune_experiment.py -- --address=localhost:6379
 
     # Start a cluster and run an experiment in a detached tmux session,
     # and shut down the cluster as soon as the experiment completes.
     # In `tune_experiment.py`, set `tune.run(upload_dir="s3://...")` to persist results
-    $ ray submit CLUSTER.YAML --tmux --start --stop tune_experiment.py  --args="--address=localhost:6379"
+    $ ray submit CLUSTER.YAML --tmux --start --stop tune_experiment.py -- --address=localhost:6379
 
     # To start or update your cluster:
     $ ray up CLUSTER.YAML [-y]
diff --git a/python/ray/scripts/scripts.py b/python/ray/scripts/scripts.py
index 8b04929b4..5b244e295 100644
--- a/python/ray/scripts/scripts.py
+++ b/python/ray/scripts/scripts.py
@@ -753,9 +753,14 @@ def rsync_up(cluster_config_file, source, target, cluster_name, all_nodes):
     type=int,
     help="Port to forward. Use this multiple times to forward multiple ports.")
 @click.argument("script", required=True, type=str)
-@click.option("--args", required=False, type=str, help="Script args.")
+@click.option(
+    "--args",
+    required=False,
+    type=str,
+    help="(deprecated) Use '-- --arg1 --arg2' for script args.")
+@click.argument("script_args", nargs=-1)
 def submit(cluster_config_file, docker, screen, tmux, stop, start,
-           cluster_name, port_forward, script, args):
+           cluster_name, port_forward, script, args, script_args):
     """Uploads and runs a script on the specified cluster.
 
     The script is automatically synced to the following location:
@@ -763,9 +768,16 @@ def submit(cluster_config_file, docker, screen, tmux, stop, start,
         os.path.join("~", os.path.basename(script))
 
     Example:
-        >>> ray submit [CLUSTER.YAML] experiment.py --args="--smoke-test"
+        >>> ray submit [CLUSTER.YAML] experiment.py -- --smoke-test
     """
     assert not (screen and tmux), "Can specify only one of `screen` or `tmux`."
+    assert not (script_args and args), "Use -- --arg1 --arg2 for script args."
+
+    if args:
+        logger.warning(
+            "ray submit [yaml] [script.py] --args=... is deprecated and "
+            "will be removed in a future version of Ray. Use "
+            "`ray submit [yaml] script.py -- --arg1 --arg2` instead.")
 
     if start:
         create_or_update_cluster(cluster_config_file, None, None, False, False,
@@ -775,7 +787,9 @@ def submit(cluster_config_file, docker, screen, tmux, stop, start,
     rsync(cluster_config_file, script, target, cluster_name, down=False)
 
     command_parts = ["python", target]
-    if args is not None:
+    if script_args:
+        command_parts += list(script_args)
+    elif args is not None:
         command_parts += [args]
 
     port_forward = [(port, port) for port in list(port_forward)]