# Overview

The powerful Graphics Processing Unit (GPU) VMs excel at massive parallel processing. This specialized hardware best accelerates compute-intensive workloads, such as training complex AI models, machine learning inference, and high-speed 3D rendering.

Cloud GPU VMs come with predefined templates. You cannot create new templates or modify the existing templates. Use Cloud API standard operations with template read access and volume management to deploy Cloud GPU VMs. Plan your storage requirements carefully and select the best template for your use case; otherwise, you will have to use additional volumes for your storage needs.

## Cloud GPU VM configuration

### Dedicated instance specifications and configuration templates

The server sizing model allocates Cloud GPU VMs with corresponding dedicated CPU cores and RAM based on available host capacity. The architecture utilizes PCIe passthrough for direct hardware access and optimal performance.

#### Template specifications

You may choose between the following four template sizes. The templates can only be used with the Cloud GPU VMs. CPU and RAM allocate proportionally to the number of GPUs. Resources utilize dedicated cores with limited flexibility.

{% hint style="warning" %}
**Warning:** Configuration templates are created during provisioning and cannot be changed later.
{% endhint %}

The breakdown of resources is as follows:

| **Template** | **GPU Model** | **GPU Type** | **Number of GPUs** | **Dedicated CPUs** | **RAM (GiB)** | **Storage (GB)** |
| ------------ | ------------- | ------------ | ------------------ | ------------------ | ------------- | ---------------- |
| **S**        | NVIDIA H200   | H200 PCIe    | 1                  | 15                 | 267           | 1024             |
| **M**        | NVIDIA H200   | H200 PCIe    | 2                  | 30                 | 534           | 1536             |
| **L**        | NVIDIA H200   | H200 PCIe    | 4                  | 60                 | 1068          | 2048             |
| **XL**       | NVIDIA H200   | H200 PCIe    | 8                  | 127                | 2136          | 4096             |

{% hint style="info" %}
**Resource limits:** By default, you can deploy only **1 Cloud GPU VM** using the **H200–S** template. To deploy templates sized **M**, **L**, or **XL**, or to run multiple **S** instances, you must first request a resource limit increase through the [<mark style="color:blue;">IONOS Cloud Support</mark>](https://docs.ionos.com/cloud/support/general-information/contact-information).
{% endhint %}

### Dedicated resource model

* **CPU Cores:** Dedicated AMD EPYC Turin (non-shared) allocation, with a fixed ratio proportional to the number of GPUs.
* **Memory:** Fixed ratio based on host specifications.
* **Flexibility:** Static resource allocation without dynamic scaling. For more information, see [<mark style="color:blue;">Known Constraints</mark>](https://docs.ionos.com/sections-test/guides/compute-services/compute-engine/cloud-gpu-vm/overview/limitations).
* **Counters:** The use of Cloud GPU VMs' vCPU and RAM counts into existing [Virtual Data Center (VDC)](#user-content-fn-1)[^1] resource usage. However, dedicated resource usage counters are enabled for Cloud GPU VMs. These counters permit granular monitoring of vCPUs, which differ from Dedicated Core Servers for the enterprise VM instances and [<mark style="color:blue;">SSD</mark>](https://docs.ionos.com/cloud/storage-and-backup/block-storage/overview/storage-performance) block storage.

## Storage architecture and planning

### Provision boot volumes

The first connected volume serves as the boot volume, containing the operating system and required system files. Provision boot volumes with adequate capacity at the initial Cloud GPU VM provisioning, because they use fixed sizing and cannot be detached or upscaled after deployment. Any storage device, including the CD-ROM, can be selected as the boot volume. You may also boot from the network.

### Adding additional volumes

Cloud GPU VM storage separates boot volumes from data volumes. You can use additional volumes for datasets requiring expansion; these volumes scale independently to accommodate growing storage requirements without interrupting operations and can be managed independently.

### Add-on Block Storage

Additional storage volumes attached after server creation provide scalable capacity.

* **Included storage:** Cloud GPU VMs come ready with high-speed Network-attached SSD premium storage by default.
* **External storage:** You may attach up to 23 additional volumes of HDD or SSD (Standard or Premium) block storage. Added HDD and SSD devices, as well as CD-ROMs, can be unmounted and deleted any time after the Cloud GPU VM is provisioned for use. For more information, see [<mark style="color:blue;">Set Up Block Storage</mark>](https://docs.ionos.com/cloud/storage-and-backup/block-storage/how-tos/set-up-block-storage).
* **Flexibility:** These additional volumes support scaling up, detaching, and attaching independently without affecting the boot volume.

### Create and use images and snapshots

Images and snapshots can be created from and copied to direct-attached storage, block storage devices, and CD-ROM drives. Also, direct-attached storage volume snapshots and block storage volumes can be used interchangeably.

### Boot configuration

Cloud GPU VMs support flexible boot device configuration, allowing you to modify boot settings through the Cloud API. Select your preferred boot device from attached storage volumes to match operational requirements.

{% hint style="info" %}
**Note:** The platform supports only [<mark style="color:blue;">IONOS Cloud Linux images</mark>](https://docs.ionos.com/sections-test/guides/storage-and-backup/images-snapshots) at launch.
{% endhint %}

## GPU specifications

The following table provides the specifications:

| **Specification**             | **Details**                                                                                                                                                      |
| ----------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **Hardware architecture**     | Utilizes "PCIe passthrough" architecture to provide direct hardware access for optimal performance, simplified deployment, and accelerated production readiness. |
| **GPU model**                 | **Primary Offering:** High-End NVIDIA H200 GPUs                                                                                                                  |
| **Maximum GPUs per template** | 8x GPU units per server                                                                                                                                          |
| **Deployment density**        | Optimized for high-performance inference workloads                                                                                                               |

## Data security

IONOS Cloud provides SSD premium as the default attached volume for Cloud GPU VMs.

[^1]: A collection of cloud resources used for creating an enterprise-grade IT infrastructure. VDC resources include the processors, memory, disk space, and networks from which virtual machines are built.