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Create a Deep Learning VM instance by using the Google Cloud console
This page shows you how to create a Deep Learning VM Images instance
by using Google Cloud Marketplace in the Google Cloud console.
Before you begin
Sign in to your Google Cloud account. If you're new to
Google Cloud,
create an account to evaluate how our products perform in
real-world scenarios. New customers also get $300 in free credits to
run, test, and deploy workloads.
In the Google Cloud console, on the project selector page,
select or create a Google Cloud project.
Click Get started. If you see a project selection window,
choose the project in which to create the instance. If this is the first
time you've launched a Compute Engine VM, you must wait for the initial API
configuration process to complete.
On the New Deep Learning VM deployment page, enter a
Deployment name. This will be the root of your virtual machine name.
Compute Engine appends -vm to this name when naming your instance.
Select a Zone, or keep the default.
Under Machine type, select the specifications that you
want for your VM, or keep the default.
Under GPUs, select the GPU type and Number of GPUs,
or keep the default values.
If you don't want to use GPUs,
click the Delete GPU button.
You have the option to select Enable access to JupyterLab via URL
instead of SSH (Beta). Enabling this Beta feature lets you
access your JupyterLab
instance using a URL. Anyone who is in the Editor or Owner role in your
Google Cloud project can access this URL. This feature
only works in the United States, the European Union, and Asia.
Select a machine learning Framework, or keep the default.
Click Deploy.
You've just created your first Deep Learning VM instance.
After the instance is deployed, the Google Cloud console opens
the Deployment Manager page
where you can manage your
Deep Learning VM instances and other deployments.
Access your new instance
Once you've created your Deep Learning VM instance, it starts
automatically. To access it:
Go to the VM Instances page in the Google Cloud console.
Under the Name column,
click the name of your virtual machine instance.
In the Remote Access section, click the first drop-down list and
choose how you'd like to access the instance. You can choose to interact
with a graphical user interface or on the command line.
Compute Engine will propagate your SSH keys and create your user. For more
information, see Connecting to
Instances.
Stop the instance
Go to the VM Instances page in the Google Cloud console.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-09-04 UTC."],[[["\u003cp\u003eThis guide outlines how to create a Deep Learning VM instance using the Google Cloud Marketplace within the Google Cloud console, starting with the "Get started" button.\u003c/p\u003e\n"],["\u003cp\u003eUsers can customize their VM by selecting a deployment name, zone, machine type, GPU type, number of GPUs, and a machine learning framework, or they can opt for default settings.\u003c/p\u003e\n"],["\u003cp\u003eAfter deployment, the VM can be accessed via the VM Instances page, where users can choose between interacting with a graphical user interface or on the command line.\u003c/p\u003e\n"],["\u003cp\u003eThe instance can be manually stopped and started from the VM Instances page, and finally, the deployment can be deleted to avoid incurring unnecessary charges.\u003c/p\u003e\n"],["\u003cp\u003eJupyterLab access via a URL is an available beta feature in select regions, granting access to users in the Editor or Owner role within your Google Cloud project.\u003c/p\u003e\n"]]],[],null,["# Quickstart: Create a Deep Learning VM instance by using the Google Cloud console\n\nCreate a Deep Learning VM instance by using the Google Cloud console\n====================================================================\n\nThis page shows you how to create a Deep Learning VM Images instance\nby using Google Cloud Marketplace in the Google Cloud console.\n\nBefore you begin\n----------------\n\n- Sign in to your Google Cloud account. If you're new to Google Cloud, [create an account](https://console.cloud.google.com/freetrial) to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.\n- In the Google Cloud console, on the project selector page,\n select or create a Google Cloud project.\n\n | **Note**: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.\n\n [Go to project selector](https://console.cloud.google.com/projectselector2/home/dashboard)\n-\n [Verify that billing is enabled for your Google Cloud project](/billing/docs/how-to/verify-billing-enabled#confirm_billing_is_enabled_on_a_project).\n\n- In the Google Cloud console, on the project selector page,\n select or create a Google Cloud project.\n\n | **Note**: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.\n\n [Go to project selector](https://console.cloud.google.com/projectselector2/home/dashboard)\n-\n [Verify that billing is enabled for your Google Cloud project](/billing/docs/how-to/verify-billing-enabled#confirm_billing_is_enabled_on_a_project).\n\n| **Note:** This quickstart assumes that all settings will remain at their defaults. For more information about the VM options available to you, see [Choose an\n| Image](/deep-learning-vm/docs/images).\n\nCreate a new instance\n---------------------\n\n1. Go to the Deep Learning VM Cloud Marketplace page in\n the Google Cloud console.\n\n [Go to the Deep Learning VM Cloud Marketplace page](https://console.cloud.google.com/marketplace/details/click-to-deploy-images/deeplearning)\n2. Click **Get started**. If you see a project selection window,\n choose the project in which to create the instance. If this is the first\n time you've launched a Compute Engine VM, you must wait for the initial API\n configuration process to complete.\n\n3. On the **New Deep Learning VM deployment** page, enter a\n **Deployment name** . This will be the root of your virtual machine name.\n Compute Engine appends `-vm` to this name when naming your instance.\n\n4. Select a **Zone**, or keep the default.\n\n5. Under **Machine type**, select the specifications that you\n want for your VM, or keep the default.\n\n6. Under **GPUs** , select the **GPU type** and **Number of GPUs** ,\n or keep the default values.\n If you don't want to use GPUs,\n click the **Delete GPU** button.\n\n7. You have the option to select **Enable access to JupyterLab via URL\n instead of SSH (Beta)**. Enabling this Beta feature lets you\n access your JupyterLab\n instance using a URL. Anyone who is in the Editor or Owner role in your\n Google Cloud project can access this URL. This feature\n only works in the United States, the European Union, and Asia.\n\n8. Select a machine learning **Framework**, or keep the default.\n\n9. Click **Deploy**.\n\nYou've just created your first Deep Learning VM instance.\nAfter the instance is deployed, the Google Cloud console opens\nthe [Deployment Manager page](https://console.cloud.google.com/dm/deployments)\nwhere you can manage your\nDeep Learning VM instances and other deployments.\n\nAccess your new instance\n------------------------\n\nOnce you've created your Deep Learning VM instance, it starts\nautomatically. To access it:\n\n1. Go to the VM Instances page in the Google Cloud console.\n\n [Go to the VM\n Instances page](https://console.cloud.google.com/compute/instances)\n2. Under the **Name** column,\n click the name of your virtual machine instance.\n\n3. In the **Remote Access** section, click the first drop-down list and\n choose how you'd like to access the instance. You can choose to interact\n with a graphical user interface or on the command line.\n\n [](../images/dlvm-qs1.png)\n\n \u003cbr /\u003e\n\nCompute Engine will propagate your SSH keys and create your user. For more\ninformation, see [Connecting to\nInstances](/compute/docs/instances/connecting-to-instance).\n\nStop the instance\n-----------------\n\n1. Go to the VM Instances page in the Google Cloud console.\n\n [Go to the VM\n Instances page](https://console.cloud.google.com/compute/instances)\n2. Select the checkbox next to the Deep Learning VM instance.\n\n3. Click **Stop**.\n\nStart the instance\n------------------\n\nAfter an instance is created, the instance starts automatically. To start the instance\nmanually when it's stopped:\n\n1. Go to the VM Instances page in the Google Cloud console.\n\n [Go to the VM\n Instances page](https://console.cloud.google.com/compute/instances)\n2. Select the checkbox next to the Deep Learning VM instance.\n\n3. Click **Start**.\n\nClean up\n--------\n\n\nTo avoid incurring charges to your Google Cloud account for\nthe resources used on this page, follow these steps.\n\n1. Go to the Deployments page in the Google Cloud console.\n\n [Go to the\n Deployments page](https://console.cloud.google.com/dm/deployments)\n2. Select the checkbox next to the Deep Learning VM deployment.\n\n3. Click **Delete**.\n\nWhat's next\n-----------\n\n- Read a more in-depth description of this process in [Creating a\n Deep Learning VM instance from\n Google Cloud Marketplace](/deep-learning-vm/docs/cloud-marketplace).\n- Learn more about [Images, image families, and\n instances](/deep-learning-vm/docs/concepts-images)."]]
