Dedicated NVIDIA GPUs
Each Nvidia Linux Server comes with fully dedicated NVIDIA GPUs, ensuring maximum performance for AI training, 3D rendering, and computation-intensive workloads without sharing resources with other users.
Linux NVIDIA GPU Servers, GPU Linux Hosting with CUDA Support
High-performance Linux GPU servers with dedicated NVIDIA GPUs, delivering unparalleled CUDA acceleration for AI training, deep learning, 3D rendering, and large-scale scientific computing. Reliable, scalable, and optimized for demanding workloads.
Choose Your High-Performance Linux NVIDIA GPU Hosting
Top-tier GPU Linux performance starting at budget-friendly rates.
| Plans | GPU Model | CPU | Memory | Disk | Bandwidth | Price | |
|---|---|---|---|---|---|---|---|
| Advanced GPU VPS - RTX Pro 5000 | RTX Pro 5000 | 24 CPU Cores | 60GB RAM | 320GB SSD | 500Mbps Unmetered | $349.00/mo | Order Now |
| Enterprise GPU VPS - RTX Pro 6000 | RTX Pro 6000 | 32 CPU Cores | 90GB RAM | 400GB SSD | 1000Mbps Unmetered | $599.00/mo | Order Now |
Basic Dedicated GPU Server - RTX 4060 | RTX 4060 | 8-Core Xeon E5-2690 | 64GB RAM | 120GB SSD + 960GB SSD | 100Mbps Unmetered | $89.50/mo | Order Now |
| Advanced Dedicated GPU Server - RTX 3060 Ti | RTX 3060 Ti | 24-Core Dual E5-2697v2 | 128GB RAM | 240GB SSD+2TB SSD | 100Mbps Unmetered | $107.55/mo | Order Now |
| Basic Dedicated GPU Server - RTX 5060 | RTX 5060 | 24-Core Platinum 8160 | 64GB RAM | 120GB SSD+960GB SSD | 100Mbps Unmetered | $113.40/mo | Order Now |
| Advanced Dedicated GPU Server - V100 | V100 | 24-Core Dual E5-2690v3 | 128GB RAM | 240GB SSD+2TB SSD | 100Mbps Unmetered | $119.60/mo | Order Now |
| Enterprise Dedicated GPU Server - RTX A6000 | RTX A6000 | 36-Core Dual E5-2697v4 | 256GB RAM | 240GB SSD+2TB NVMe+8TB SATA | 100Mbps Unmetered | $274.50/mo | Order Now |
| Advanced Dedicated GPU Server - RTX A4000 | RTX A4000 | 24-Core Dual E5-2697v2 | 128GB RAM | 240GB SSD+2TB SSD | 100Mbps Unmetered | $279.00/mo | Order Now |
| Enterprise Dedicated GPU Server - A100 | A100 | 36-Core Dual E5-2697v4 | 256GB RAM | 240GB SSD+2TB NVMe+8TB SATA | 100Mbps Unmetered | $359.55/mo | Order Now |
| Enterprise Dedicated GPU Server - RTX 4090 | RTX 4090 | 36-Core Dual E5-2697v4 | 256GB RAM | 240GB SSD+2TB NVMe+8TB SATA | 100Mbps Unmetered | $549.00/mo | Order Now |
| Enterprise Dedicated GPU Server - RTX 5090 | RTX 5090 | 36-Core Dual E5-2697v4 | 256GB RAM | 240GB SSD+2TB NVMe+8TB SATA | 100Mbps Unmetered | $599.00/mo | Order Now |
| Enterprise Dedicated GPU Server - H100 | H100 | 36-Core Dual E5-2697v4 | 256GB RAM | 240GB SSD+2TB NVMe+8TB SATA | 100Mbps Unmetered | $2599.00/mo | Order Now |
Discover More High-Performance Linux GPU Servers.
Support and Management Features for Linux GPU server
widgetsGPU Linux Software Ecosystem Compatibility
CUDA
A parallel computing platform by NVIDIA that enables GPUs to accelerate AI training, scientific computing, and high-performance applications.
Docker
A containerization platform that allows you to package applications and dependencies for consistent deployment across environments.
Jupyter
An interactive web-based environment for writing code, running experiments, and visualizing data in real time.
Supported Linux Operating Systems for GPU Linux Servers
Choose any major Linux distribution fully optimized for Nvidia GPU performance.
| NVIDIA GPU Support | CUDA Ready | Stability | Package Management | Release Type | Recommended Use | |
|---|---|---|---|---|---|---|
| CentOS | Full | Yes | High | yum/dnf | LTS | Web hosting, Database servers, Batch processing |
| Ubuntu | Full | Yes | High | apt | LTS + Rolling | AI training, Machine learning, Data analysis |
| Debian | Full | Yes | High | apt | LTS | Stable compute nodes, Scientific computing, Web servers |
| AlmaLinux | Full | Yes | High | yum/dnf | LTS | Virtualization, Database hosting, Container workloads |
| Fedora | Full | Yes | Medium | dnf | Rolling | Development environment, Latest software testing, AI prototyping |
| openSUSE | Full | Yes | Medium | zypper | Rolling | Workstations, Software development, GPU-accelerated experiments |
If you need a Linux distribution not listed here, contact our support team and we’ll help you set up the perfect GPU Linux environment.
GPU Linux vs. GPU Windows – Which Is Right for Your Workloads?
Compare performance, compatibility, and flexibility to choose the best environment for your needs.
| GPU Linux | GPU Windows | |
|---|---|---|
| CUDA Support | Full support, optimized for AI & ML workloads | Supported, but some frameworks may require extra setup |
| AI / ML Frameworks | TensorFlow, PyTorch, Jupyter, Docker fully supported | TensorFlow and PyTorch supported, limited Docker integration |
| Performance | Higher efficiency and lower overhead | Slightly higher system resource usage |
| Package Management | apt, yum, dnf, zypper | Limited, mostly manual installs |
| Customization | Highly flexible, ideal for scripting and automation | Limited flexibility, GUI focused |
| Stability | Very stable for long-running GPU workloads | Stable, but updates can interfere with GPU tasks |
| Cost Efficiency | Open-source OS, lower licensing costs | No license included |
| Recommended Use | AI training, deep learning, ML, data analytics, HPC | Gaming, Windows-native software, light AI/ML experiments |
GPU Linux delivers maximum performance and full AI/ML readiness, while GPU Windows is ideal for Windows-native software and GUI workflows.
What You Can Do with Linux GPU Servers
Boost AI training, real-time inference, and compute-intensive tasks with scalable GPU servers.
AI & Machine Learning Training
Linux GPU Servers accelerate deep learning training for image recognition, NLP, and recommendation systems. GPU parallel processing makes training faster than CPUs, ideal for AI developers, researchers, and data teams.
Real-Time AI Predictions
Deploy trained models on GPU Linux servers for low-latency, high-throughput inference. Perfect for chatbots, image or speech recognition, and recommendation systems, ensuring fast and reliable AI responses.
Scientific & Data Computing
Linux GPU Servers excel at complex simulations, climate modeling, and financial risk analysis. GPUs handle large datasets and heavy computations efficiently, boosting performance for research and enterprise analytics.
3D Rendering & Video Processing
GPU servers speed up 3D rendering, video transcoding, and VFX production while supporting high-resolution output. Animation studios, post-production teams, and game developers can complete projects faster and more efficiently.
Accelerated App & Algorithm Development
The stable Linux GPU environment supports Docker, Kubernetes, and Jupyter Notebook. Developers can build high-performance apps, parallel algorithms, and GPU databases with improved efficiency and computational power.
Scalable AI SaaS & Model Hosting
Linux GPU Servers support high-concurrency AI SaaS and model API services. They allow flexible resource scaling and stable operation, providing reliable and fast AI computing for startups and enterprise platforms.
| Recommended GPUs | Why It Works | |
|---|---|---|
| AI & Machine Learning Training | H100, A100, RTX Pro 6000, RTX A6000 | These GPUs feature massive memory, dense Tensor Cores, and high FP32/BF16 compute power, enabling efficient training of large-scale models and distributed AI workloads. |
| Real-Time AI Inference / Low-Latency Services | RTX 5090, RTX 4090, RTX A4000 | With high CUDA and Tensor Core counts combined with fast memory, these GPUs deliver rapid model inference and consistent low-latency performance for real-time applications. |
| Scientific Computing & Data Analysis | V100, A100, H100 | Their high-precision compute capabilities and large memory allow efficient execution of large-scale matrix operations, scientific simulations, and complex data analytics. |
| 3D Rendering & Video Processing | RTX 4090, RTX 5090, RTX Pro 6000, RTX A6000 | The combination of many CUDA cores, Tensor Cores, and large memory enables fast rendering of complex scenes, high-resolution video processing, and AI-accelerated denoising. |
| Accelerated App & Algorithm Development | RTX 3060 Ti, RTX 4060, RTX 5060 | These GPUs offer moderate memory and solid compute performance, providing cost-effective acceleration for development, prototyping, and algorithm testing. |
| Scalable AI SaaS & Model Hosting | A100, H100, RTX Pro 5000, RTX A5000 | Large memory, strong compute power, and multi-instance virtualization allow these GPUs to reliably host multiple models and support multi-tenant AI services. |
Why Choose Database Mart Linux GPU Server
Experience outstanding performance, reliability, and flexibility with Database Mart Linux GPU Servers.
Wide Linux Distribution Support
Our Linux GPU servers support all major Linux distributions, including Ubuntu, CentOS, Debian, and Fedora, enabling seamless deployment of your applications and development environments.
High-Speed Network
Each Linux GPU is equipped with high-speed, low-latency networking, ensuring smooth data transfer, real-time model inference, and uninterrupted operation for large-scale or latency-sensitive workloads.
Secure & Reliable
GPU Linux servers provide comprehensive security measures such as firewall, strict access control, and continuous monitoring, ensuring that your data remain fully protected and highly reliable.
Customizable Configurations
Our GPU Linux servers offer fully customizable configurations for GPU count, memory, storage, and network bandwidth, allowing you to tailor each instance precisely to the demands of your different projects.
24/7/365 Expert Support
Our Linux GPU servers are backed by technical experts available 24/7/365 to assist with setup, maintenance, and software configuration, ensuring uninterrupted operation and professional support.
Related Guides & Tutorials for Linux GPU
Master Linux GPU environments with practical guides, performance tuning tips, and step-by-step tutorials.
Top 3 Linux GPU Monitoring Command Line Tools
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How to install Stable Diffusion WebUI AUTOMATIC1111 on Linux
This tutorial walks through how to install AUTOMATIC1111 on Linux Ubuntu, so that you can use stable Diffusion to generate AI images on your PC.
How to install CUDA, CUDNN and TensorFlow in GPU Server
This article will show you how to install CUDA 10.0 + cudnn 7.6 + keras 2.3.1 + tensorflow 1.15.2 + python 3.7.10 in Ubuntu 18 OS. In other Linux OS, the KB is not suitable.
FAQ about GPU Linux Server
Find answers to common questions about our Linux GPU servers.
What is a GPU Linux server?
A GPU Linux server is a high-performance computing environment powered by GPUs and optimized Linux systems.
Does your server support NVIDIA GPUs?
Yes, our Nvidia Linux servers fully support linux nvidia environments with optimized drivers and configurations, ensuring seamless performance for GPU-intensive applications and frameworks.
Is CUDA supported on your GPU Linux servers?
Absolutely. We provide full compatibility with linux nvidia cuda, allowing you to run CUDA-based applications such as machine learning frameworks and parallel computing workloads with ease.
Which Linux distributions are available?
We support multiple mainstream Linux distributions, including ubuntu nvidia and fedora nvidia environments, giving you flexibility to choose the system that best fits your workflow.
Can I try the GPU Linux server before purchasing?
Yes, we offer a free trial option so you can test our Linux GPU server performance in real-world scenarios. This allows you to evaluate speed, stability, and compatibility before making a commitment.
Experience High-Performance GPU Linux Servers Today
Start your journey with a powerful GPU Linux environment today. Whether you're running AI models, leveraging linux nvidia cuda, or deploying production workloads, our Linux GPU server delivers the performance and stability you need.