Dedicated NVIDIA GPUs with bare-metal passthrough. Train models, run inference, render video, and accelerate scientific computing on demand.
+-------------------------+
| NVIDIA-SMI 550.54.15 |
| Driver: 550.54.15 |
| CUDA Version: 12.4 |
+-------------------------+
| GPU Name | Mem |
| 0 Tesla P40 | 24GB |
+-------------------------+
| GPU Util: 0% |
| Memory: 0MiB / 24576MiB|
+-------------------------+
$ python train.py --model llama
Loading model... _
Dedicated NVIDIA GPUs with full PCIe passthrough for maximum performance
We are actively expanding our GPU fleet. Additional NVIDIA GPU models with higher VRAM and newer architectures will be available soon.
Need enterprise-grade GPUs (A100, H100) or multi-GPU configurations? Contact us to discuss your requirements.
From training neural networks to rendering 3D scenes, GPU VPS handles it all
Train deep learning models with PyTorch, TensorFlow, or JAX. Fine-tune large language models like LLaMA, Mistral, and Stable Diffusion on dedicated GPU hardware.
Get Started →Deploy AI models in production with low-latency GPU inference. Serve LLMs, image generation, speech recognition, and computer vision APIs at scale.
Get Started →Accelerate video transcoding with NVENC, render 3D scenes with Blender or Maya, and process high-resolution media pipelines with GPU-accelerated encoding.
Get Started →Run molecular dynamics, climate simulations, computational fluid dynamics, and other HPC workloads accelerated by CUDA-enabled GPUs.
Get Started →Accelerate data pipelines with RAPIDS, cuDF, and cuML. Process large datasets, run GPU-accelerated analytics, and build real-time data processing workflows.
Get Started →Build and iterate on AI applications with Jupyter notebooks, VS Code remote, and full CUDA development environments. Prototype faster with dedicated GPU resources.
Get Started →Direct PCIe passthrough means zero virtualization overhead. Your code talks directly to the GPU hardware.
No complex reservations or sales calls. Select your GPU, choose an OS, and deploy in minutes.
Monthly billing with no lock-in contracts. Scale up when you need GPUs, scale down when you don\u0027t.
Install any framework, driver version, or CUDA toolkit. Your server, your rules. SSH access from day one.
Pre-configured guides for popular AI/ML frameworks, creative tools, and GPU-accelerated applications
Everything you need to know about GPU VPS hosting
A GPU VPS is a virtual private server equipped with dedicated NVIDIA GPU hardware. It provides the same flexibility as a standard VPS but with powerful parallel processing capabilities for AI/ML training, inference, rendering, and scientific computing workloads.
We currently offer NVIDIA Tesla P40 GPUs with 24GB of VRAM each. These GPUs excel at AI/ML inference, model fine-tuning, video transcoding, and scientific computing. Additional GPU models will be added as we expand our infrastructure.
GPU passthrough gives your VPS direct, bare-metal access to the physical GPU hardware. Unlike shared or virtualized GPUs, you get the full performance of the GPU with no overhead. Your applications interact with the GPU exactly as they would on a dedicated machine.
GPU VPS instances come with Ubuntu and the option to have NVIDIA drivers and CUDA toolkit pre-installed. You can also install your preferred driver version manually. We provide documentation for setting up popular ML frameworks like PyTorch and TensorFlow.
Yes, you can attach multiple GPUs to a single VPS for workloads that benefit from multi-GPU training or parallel processing. Contact our sales team for multi-GPU configurations and pricing.
GPU VPS is ideal for AI/ML model training and inference, large language model fine-tuning, computer vision, video transcoding and rendering, scientific simulations, and any workload that benefits from massive parallel processing power.
GPU VPS is billed on a monthly basis, just like our standard VPS plans. You only pay for the time your server is provisioned. Contact us for current pricing as we finalize our GPU tier offerings.
GPU VPS instances run on dedicated GPU-equipped hardware, so upgrading from a standard VPS requires provisioning a new server. However, you can easily migrate your data and configurations. Our support team can assist with the migration process.
Yes, all VPS plans including GPU VPS come with network-level DDoS protection, full root access, IPv4 and IPv6 connectivity, and the same security features as our standard cloud VPS offering.
GPU VPS is available with Ubuntu 22.04 LTS and Ubuntu 24.04 LTS, which have the best NVIDIA driver support. Debian 12 is also supported. We recommend Ubuntu 24.04 LTS for the latest CUDA toolkit compatibility.
No, there is no minimum commitment. GPU VPS is billed monthly and you can cancel anytime. We believe in flexible, no-lock-in cloud computing.
Simply create an account, select a GPU VPS configuration, choose your operating system, and deploy. Your GPU-powered server will be ready in minutes with full root access and your GPU available via nvidia-smi.
Get dedicated NVIDIA GPU power in minutes. No reservations, no sales calls.