How to Provision Vultr Cloud GPU Instances

Navigate to Products and select Compute on the list of product options.

Click Deploy to access the Deploy New Instance page.

Select Cloud GPU.

Choose your desired Vultr location to deploy the instance.

Select a cloud image to install on your instance based on the following options:

• Marketplace Apps: Install a prebuilt software stack or application and the recommended operating system image on the instance.
• Operating System: Install a fresh operating system image on the instance.
• Upload ISO: Install a specific ISO available in your Vultr account or upload a new ISO image from your workstation to install on the instance.
• ISO Library: Install a specific ISO image from the Vultr ISOs library.
• Backup: Recover a specific backup available in your Vultr account to the instance.
• Snapshot: Install a specific snapshot available in your Vultr account to the instance.

Select the instance specifications based on the following GPU type, vCPU, storage, bandwidth, and memory options:

• NVIDIA A100:Suitable for AI, data analytics, and HPC workloads.
• NVIDIA A40: Suitable for professional graphics and AI workloads.
• NVIDIA A16: Suitable for virtual desktops and workstations that require GPU power and performance.

Select optional Additional Features to enable on your instance.

• Auto Backups: Enables automatic backups to enable data recovery incase the instance fails.
• IPV6: Assigns a public IPV6 address to the instance.
• DDoS Protection: Enables an extra security layer to prevent potential Distributed Denial of Service (DDoS) attacks on your instance.
• Cloud-Init User-Data: Enables the Cloud-Init data to run at the instance's initialization stage.

Select optional Server Settings to activate on the instance.

• SSH Keys: Installs a specific SSH key from your Vultr account to the instance.
• Firewall Group: Activates a Vultr Firewall group to filter incoming network traffic on the instance.

Optional: Select existing SSH keys to enable on your instance. Choose a Vultr firewall group to filter the instance traffic and click the IP Address drop-down to attach a reserved IP to your instance.

Enter a new hostname in the Server Hostname field and a descriptive label in the Server Label field to apply on the instance.

View the server quantity and the cost summary. Then, click Deploy Now to create the instance on your Vultr account.

Send a POST request to the Create Instance endpoint to create a new instance with a specific plan, operating system, and hostname in a specific Vultr location.

$ curl "https://api.vultr.com/v2/instances" \
  -X POST \
  -H "Authorization: Bearer ${VULTR_API_KEY}" \
  -H "Content-Type: application/json" \
  --data '{
    "region" : "<vultr-location>",
    "plan" : "<gpu-instance-plan>",
    "os_id" : <os-id>,
    "label" : "<instance-label>",
    "hostname": "<hostname>",
  }'

Visit the Create Instance API page to view additional attributes to add to apply on the Cloud GPU instance.

Create a new Cloud GPU instance with a specific plan, operating system, and hostname in a specific Vultr location.

$ vultr-cli instance create --region <vultr-location> --plan <gpu-instance-plan> --os <os-id>  --label <instance-label> --host <hostname>

Run vultr-cli instance create --help to view additional options to apply on the Cloud GPU instance.

Ensure the Vultr Terraform provider is configured in your Terraform project.

Add the Cloud GPU instance resource to your Terraform configuration.

terraform {
    required_providers {
        vultr = {
            source  = "vultr/vultr"
            version = "~> 2.26"
        }
    }
}

provider "vultr" {}

resource "vultr_instance" "gpu" {
    region      = "del"              # Target deployment region
    plan        = "vcg-a100-1c-85gb" # Cloud GPU plan ID (A100/A40/A16)
    os_id       = 2284               # Ubuntu 24.04 LTS x64
    label       = "gpu-instance-1"
    hostname    = "gpu-instance-1"
    enable_ipv6 = true
}

output "public_ip" {
    value = vultr_instance.gpu.main_ip
}

Apply the configuration and observe the following output:

Apply complete! Resources: 1 added, 0 changed, 0 destroyed.