This page shows you how to create a Deep Learning VM Images instance
from Cloud Marketplace within the
Google Cloud console without using the command line.

## Before you begin

1. [Choose a specific Deep Learning VM
   image to use](https://docs.cloud.google.com/deep-learning-vm/docs/images). Your choice depends on your preferred framework and processor type.
2. If you are using GPUs with your Deep Learning VM, check the [quotas page](https://console.cloud.google.com/quotas) to ensure that you have enough GPUs available in your project. If GPUs are not listed on the quotas page or you require additional GPU quota, [request a
   quota increase](https://docs.cloud.google.com/compute/quotas#requesting_additional_quota).

## Creating an instance

1. Go to the Deep Learning VM Cloud Marketplace page in
   the Google Cloud console.

   [Go to the Deep Learning VM Cloud Marketplace page](https://console.cloud.google.com/marketplace/details/click-to-deploy-images/deeplearning)
2. Click **Get started**.

3. Enter a **Deployment name** , which will be the root of your VM name.
   Compute Engine appends `-vm` to this name when naming your instance.

4. Select a **Zone**.

5. Under **Machine type** , select the specifications that you
   want for your VM.
   [Learn more about machine types.](https://docs.cloud.google.com/compute/docs/machine-types)

6. Under **GPUs** , select the **GPU type** and **Number of GPUs** .
   If you don't want to use GPUs,
   click the **Delete GPU** button
   and skip to step 7. [Learn more about GPUs.](https://docs.cloud.google.com/gpu)

   1. Select a **GPU type** . Not all GPU types are available in all zones. [Find a combination that is supported.](https://docs.cloud.google.com/compute/docs/gpus)
   2. Select the **Number of GPUs** . Each GPU supports different numbers of GPUs. [Find a combination that is supported.](https://docs.cloud.google.com/compute/docs/gpus)
7. Select a machine learning **Framework**.

8. If you're using GPUs, an NVIDIA driver is required.
   You can install the driver
   yourself, or select **Install NVIDIA GPU driver automatically
   on first startup**.

9. 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.
   Currently, this feature only works in
   the United States, the European Union, and Asia.

10. Select a boot disk type and boot disk size.

11. Select the networking settings that you want.

12. Click **Deploy**.

If you choose to install NVIDIA drivers, allow 3-5 minutes for installation
to complete.

After the VM is deployed, the page updates with instructions for
accessing the instance.

## What's next

For instructions on connecting to your new Deep Learning VM instance
through the Google Cloud console or command line, read [Connecting to
Instances](https://docs.cloud.google.com/compute/docs/instances/connecting-to-instance). Your instance name
is the **Deployment name** you specified with `-vm` appended.