# GPU VPS Hosting with a Dedicated NVIDIA GPU

> Run AI inference, model training, image generation and CUDA workloads on a VPS with its own NVIDIA GPU, full root access and unmetered bandwidth in a US data center. Billed monthly, with free setup.

- Page: https://ownwebservers.com/gpu-vps
- Order online: https://ownwebservers.com/serviceinfo/index.php?rp=/store/ai-and-gpu-vps-server

## AI Powered Hosting Packages

Four GPU VPS plans, from a Quadro P1000 for light CUDA work to an RTX PRO 4000 with 24 GB of VRAM for larger models.

- Dedicated NVIDIA GPU
- Full root access
- 1 dedicated IPv4
- DDoS protection
- Free setup

| Plan | GPU | vCPU | RAM | Storage | Bandwidth | Price | Order |
|---|---|---|---|---|---|---|---|
| Express GPU VPS | Quadro P1000 · 2 GB VRAM | 8 cores | 16 GB | 120 GB SSD | 100 Mbps unmetered | $45/mo | https://ownwebservers.com/serviceinfo/cart.php?a=add&pid=229 |
| Basic GPU VPS | RTX 5060 · 8 GB VRAM | 16 cores | 28 GB | 240 GB SSD | 500 Mbps unmetered | $139/mo | https://ownwebservers.com/serviceinfo/cart.php?a=add&pid=230 |
| Professional GPU VPS | RTX A4000 · 16 GB VRAM | 24 cores | 28 GB | 320 GB SSD | 1 Gbps unmetered | $179/mo | https://ownwebservers.com/serviceinfo/cart.php?a=add&pid=231 |
| Advanced GPU VPS – RTX Pro 4000 | RTX PRO 4000 · 24 GB VRAM | 24 cores | 56 GB | 320 GB SSD | 1 Gbps unmetered | $289/mo | https://ownwebservers.com/serviceinfo/cart.php?a=add&pid=232 |

## Which GPU VPS Fits Your Workload?

GPU memory (VRAM) decides which models fit, so start there. CPU, RAM and storage grow with each plan.

| Plan | GPU | Good for | Price |
|---|---|---|---|
| Express GPU VPS | Quadro P1000 · 2 GB VRAM | Learning CUDA, light GPU compute, video encoding and small computer-vision models. | $45/mo |
| Basic GPU VPS | RTX 5060 · 8 GB VRAM | Stable Diffusion image generation, and small LLMs such as 7B–8B models with 4-bit quantization. | $139/mo |
| Professional GPU VPS | RTX A4000 · 16 GB VRAM | SDXL, LLMs up to about 13B with 4-bit quantization, and LoRA fine-tuning of smaller models. | $179/mo |
| Advanced GPU VPS – RTX Pro 4000 | RTX PRO 4000 · 24 GB VRAM | Larger quantized LLMs (around 30B at 4-bit), longer contexts and heavier inference APIs. | $289/mo |

Typical guidance only. Whether a model fits depends on its size, quantization, context length, batch size and framework.

## GPU VPS Servers at Affordable Pricing

Run AI training, inference, notebooks and GPU containers on a dedicated NVIDIA GPU with full root access. Choose your operating system and deploy with JupyterLab, CloudPanel or the GPU Container Runtime pre-installed.

- Dedicated NVIDIA GPU
- NVIDIA CUDA acceleration
- Full root access
- SSD storage
- Unmetered bandwidth
- 1 dedicated IPv4
- DDoS protection
- Free setup

### Supported Operating Systems

Deploy your GPU VPS on the Linux distribution your team already knows.

- Ubuntu: 22.04 LTS, 24.04 LTS, 26.04 LTS
- AlmaLinux: 8, 9
- Debian: 11, 12

### Deploy with Pre-installed Applications

Start working the moment your server is ready. Each GPU VPS can be deployed with JupyterLab, CloudPanel or the GPU Container Runtime already installed.

#### JupyterLab (Development interface)

JupyterLab is the open-source, browser-based environment from Project Jupyter for notebooks, code, terminals and data. Explore datasets, prototype models and visualise results right next to the GPU, without setting up a local workstation.

- Notebooks, code editor and terminal in one browser tab
- Run Python and other Jupyter kernels on your server
- Ideal for experiments, data exploration and model prototyping

#### CloudPanel (Server management)

CloudPanel is a free server control panel for hosting PHP, Node.js and Python applications, static sites and reverse proxies. Publish the API or web app in front of your model with a domain, free Let’s Encrypt SSL and a database, from one dashboard.

- Sites, databases and users managed from a web dashboard
- Free Let’s Encrypt SSL certificates
- Runs on Ubuntu and Debian

#### GPU Container Runtime (Container infrastructure)

The NVIDIA Container Toolkit lets Docker and other container runtimes use the server’s NVIDIA GPU. Run GPU-accelerated container images, such as framework images with CUDA libraries, and keep every project’s dependencies isolated.

- GPU access inside Docker containers
- Package each model with its own CUDA and framework versions
- Move the same image between development and production

### How They Relate

The three work at different layers and are often used together: the container runtime gives your workloads the GPU, JupyterLab is where you write and test code, and CloudPanel publishes the finished app with a domain and SSL.

| Component | Layer / role | Main purpose |
|---|---|---|
| JupyterLab | Development interface | Write and run notebooks and code interactively in a browser |
| CloudPanel | Server management | Manage websites, apps, databases, SSL and server resources |
| GPU Container Runtime | Container infrastructure | Give containers access to NVIDIA GPUs and CUDA |

### How our GPU pricing compares

| Provider / plan | GPU (VRAM) | Type | Published price | Per month, 24/7 | Setup fee | US data center |
|---|---|---|---|---|---|---|
| OwnWebServers Professional GPU VPS | NVIDIA RTX A4000 (16 GB) | GPU VPS | $179/mo | $179 | Free | Yes |
| OwnWebServers Advanced GPU VPS – RTX Pro 4000 | NVIDIA RTX PRO 4000 (24 GB) | GPU VPS | $289/mo | $289 | Free | Yes |
| Hetzner GEX45 | NVIDIA RTX PRO 4000 Blackwell SFF (24 GB) | Dedicated server | €214.00/mo excl. VAT | As published | €209.00 | No (EU only) |
| DigitalOcean GPU Droplet | NVIDIA RTX 4000 Ada (20 GB) | Virtual (cloud) | $0.76/GPU/hr | ~$555* | None | No (Toronto only) |
| Lambda 1x Quadro RTX 6000 | NVIDIA Quadro RTX 6000 (24 GB) | Virtual (cloud) | $0.69/GPU/hr + sales tax | ~$504* | None | Yes |

Competitor list prices from each provider's official pricing page, checked October 21, 2026; they may have changed since. \*Hourly price × 730 hours (24/7 use). Specs differ between plans. Sources: https://www.hetzner.com/dedicated-rootserver/gex45/, https://www.digitalocean.com/pricing/gpu-droplets, https://lambda.ai/pricing

## Need Something Different?

- [GPU Dedicated Servers](https://ownwebservers.com/gpu-servers.md): A whole bare-metal server with up to an RTX 5090, for training runs and multi-user workloads.
- [AI Powered Hosting](https://ownwebservers.com/ai-hosting.md): Hosting for AI agents, LLM-powered apps and machine learning projects, on the same GPU VPS plans.

## GPU VPS FAQs

### What is a GPU VPS?

A GPU VPS is a virtual private server with an NVIDIA GPU attached. You get root access to your own Linux server, plus a GPU for CUDA workloads such as AI inference, training and image generation.

### Is the GPU shared with other customers?

No. Every GPU VPS plan includes a dedicated NVIDIA GPU for your server.

### How much VRAM do I need?

VRAM decides which models fit. As a rough guide, 8 GB runs Stable Diffusion and 7B–8B LLMs with 4-bit quantization, 16 GB handles SDXL and models up to about 13B, and 24 GB fits quantized models of around 30B. The exact fit depends on the model and its settings.

### What is the difference between a GPU VPS and a GPU dedicated server?

A GPU VPS gives you a fixed share of a server’s CPU, RAM and storage with a dedicated GPU, at a lower monthly price. A GPU dedicated server gives you the whole machine, with more powerful GPUs such as the RTX 5090.

### Where are GPU VPS servers located?

GPU VPS plans run in our US data centers.

### Which operating systems can I run on a GPU VPS?

You can deploy Ubuntu 22.04, 24.04 or 26.04 LTS, AlmaLinux 8 or 9, or Debian 11 or 12.

### Which applications can be pre-installed on a GPU VPS?

Your GPU VPS can be deployed with JupyterLab for notebooks and interactive code, CloudPanel for managing websites, apps, databases and SSL, or the GPU Container Runtime (NVIDIA Container Toolkit) for running GPU-accelerated containers.

### Which operating systems support CloudPanel?

CloudPanel runs on Ubuntu and Debian. If you want CloudPanel pre-installed, choose one of those operating systems.

### What does the GPU Container Runtime do?

It is the NVIDIA Container Toolkit, which lets Docker containers use the server’s NVIDIA GPU. You can then run GPU-accelerated container images, such as framework images with CUDA libraries, with each project isolated in its own container.

### How is a GPU VPS billed?

GPU VPS plans are billed monthly, in advance. Quarterly, semi-annual, annual and biennial terms are also available at checkout.

## Contact & ordering
- Provider: OwnWebServers — https://ownwebservers.com
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