Dedicated Server with GPU
for AI, Rendering & Gaming
Deploy high-performance GPU dedicated servers powered by RTX 4090, A100, H100, and enterprise-grade NVIDIA GPUs. Get bare metal resources, NVMe storage, full root access, and high-bandwidth connectivity for AI training, rendering, simulations, VDI, and GPU-intensive workloads.
✅ RTX 4090, A100 & H100 GPU Servers
✅ Full Root / Admin Access
✅ NVMe SSD Storage
✅ 1Gbps–10Gbps Network Options
✅ Windows & Linux Support
✅ Fast Global Deployment
GPU Dedicated Server Plans and Pricing
Choose from high-performance GPU dedicated server configurations optimized for AI workloads, rendering, virtualization, and GPU acceleration. Custom GPU server quotes are also available for enterprise deployments and multi-GPU environments.
Price from 355$ to 723$ \ Storage from 480GB to 1024GB
Netherlands
| Name | CPU | RAM | Storage | Traffic/Port | Price | Action |
|---|---|---|---|---|---|---|
| DGS i9-9900K_1080Ti | 1xIntel i9-9900K(8cores/3.6GHz) | 64 GB | 480GB SSD | Upto 50TB/1Gbits | 310.00$ / Monthly | Order Now |
| DGS Ryzen 7950x_RTX 4090 24GB | Ryzen 7950X (16cores/4.5GHz) | 128 GB | 1TB NVMe | Upto 50TB/1Gbits | 637.00$ / Monthly | Order Now |
| DGS Ryzen 5950x_RTX 3090 24GB | Ryzen 5950X (16cores/3.4GHz) | 128 GB | 1TB NVMe | Upto 50TB/1Gbits | 399.00$ / Monthly | Order Now |
TrustScore: 4.6 | 21,420 reviews 
TrustScore: 4.7 | 1,420 reviews 
TrustScore: 4.6 | 21,420 reviews 
TrustScore: 4.7 | 1,237 reviews What Is a GPU Dedicated Server?
A GPU dedicated server is a physical server with dedicated GPUs built for high-performance workloads. Unlike shared hosting, all resources are fully reserved for one user.
These servers are widely used for AI training, deep learning, 3D rendering, simulations, remote workstations, and other compute-intensive tasks.
Every GPU Dedicated Server Includes
Choose between Linux or Windows GPU dedicated servers, managed or unmanaged dedicated GPU hosting, and multiple global locations. To ensure maximum reliability and performance, every GPU dedicated server from 1Gbits comes with:
Enterprise-Grade GPUs
NVIDIA RTX™ and AMD GPU options optimized for AI, rendering, and parallel computing.
100% Dedicated Hardware
No resource sharing — with managed dedicated servers, you have full control over CPU, GPU, RAM, and storage. For CPU-heavy workloads, explore Ryzen Dedicated Servers and High-End Dedicated Servers.
High-Bandwidth Connectivity
Low-latency network routes with unmetered traffic options across multiple data center locations.
Full Root/Admin Access
Install and configure your environment as needed with complete administrative control.
Instant Deployment
Automated provisioning ensures fast delivery so you can start using your dedicated GPU server without delays.Need fast setup? Explore our Instant Dedicated Server solutions.
24/7 Expert Support
Our technical team is available around the clock to assist with setup, optimization, and troubleshooting.
Why Choose 1Gbits for GPU Dedicated Hosting
Reliable GPU infrastructure built for compute-heavy workloads, enterprise deployments, and professional GPU acceleration.
Enterprise GPU Hardware
Deploy servers powered by RTX 3090, RTX 4090, A100, H100, and other professional GPU models suitable for AI, rendering, and HPC workloads.
Full Root or Admin Access
Install custom drivers, CUDA versions, frameworks, containers, and operating systems with complete administrative control.
100% Dedicated Bare Metal Resources
All GPU, CPU, RAM, and storage resources are fully dedicated to your workloads with no shared virtualization overhead.
Fast Deployment
GPU dedicated servers are deployed quickly to help reduce downtime and accelerate project delivery timelines.
High-Bandwidth Global Network
Benefit from premium international routing, high-speed connectivity, and stable bandwidth options for data-heavy GPU applications.
Security, Compliance, and Reliability
Enterprise-grade infrastructure, redundant networking, and stable hardware environments help support production-ready workloads.
Best GPU Dedicated Servers by Use Case
From artificial intelligence to multimedia processing, GPU dedicated servers power today’s most compute-intensive industries. Here are the most common applications:
AI Training and Deep Learning
AI workloads need GPUs with high CUDA cores and large VRAM. GPUs like the RTX 4090, A100, and H100 are popular for AI training, LLMs, and computer vision.
Fast NVMe storage and strong CPUs also improve dataset loading and overall performance.
AI Inference and Production Serving
Inference workloads focus on low latency and efficient GPU performance. GPU dedicated servers are commonly used for AI APIs, image processing, and production deployments.
RTX 3090 and RTX 4090 servers are strong choices for medium-to-large inference workloads.
3D Rendering and Video Encoding
GPU rendering in Blender, Octane, Unreal Engine, and video software runs much faster with RTX GPUs, improving workflow efficiency.
Fast NVMe storage also helps with quicker loading and smoother rendering.
VDI and Remote Workstations
GPU-powered VDI lets designers and engineers access high-performance remote workstations from anywhere. Windows GPU servers are widely used for CAD, 3D modeling, and creative work.
Dedicated GPUs provide smooth performance and low latency.
Scientific Computing and Simulations
Scientific workloads and simulations run much faster with GPU acceleration. A100 and H100 servers are popular for research and HPC tasks, while multi-GPU setups handle larger compute workloads efficiently.
Gaming and GPU-Accelerated Workloads
GPU dedicated servers are ideal for game streaming, rendering, virtualization, and other graphics-heavy workloads. RTX GPUs deliver strong real-time graphics performance and acceleration.
Features of 1Gbits's GPU Dedicated Servers
Experience unparalleled performance with 1Gbits' GPU dedicated server hosting. Engineered to excel in AI workloads like image recognition and data analysis, our servers are optimized for speed, efficiency, and scalability. Dedicated Server GPU provides the computational power you need to drive innovation and growth.
Unmatched Performance
Our GPU servers are built to handle intensive AI workloads, delivering exceptional computing power optimized for tasks like image recognition, natural language processing, and complex data analysis.
Scalability
Easily scale your resources as your AI projects grow. From startups to enterprises, our servers offer flexibility to accommodate increasing computational demands.
Enhanced Security
Your data's security is our priority. With GDPR-compliant practices and robust physical and cyber security measures, rest assured your information is safe with us.
Energy Efficiency
Designed with energy-efficient components, our servers minimize power consumption while maximizing performance, helping you reduce operational costs without compromising on speed.
Dedicated Resources
Enjoy exclusive access to GPU resources. A dedicated server with GPU ensures consistent performance and eliminates resource contention common in shared environments.
Expert Support
Need assistance? Our dedicated support team is available 24/7 to help you set up, optimize, and troubleshoot your server, ensuring smooth operation at all times.
How a Dedicated GPU Server Works
A dedicated GPU server combines powerful CPUs, fast RAM, NVMe storage, and one or more NVIDIA or AMD GPUs in a single machine. It speeds up heavy workloads by offloading parallel processing tasks to the GPU.
GPU servers are ideal for AI training, Blender rendering, CUDA applications, and GPU virtualization.
- GPU Acceleration: GPU dedicated servers include built-in GPU acceleration for handling parallel tasks, while regular dedicated servers mainly rely on CPU power.
- AI & Deep Learning: GPU servers are optimized for AI training, machine learning, and deep learning workloads. Regular servers can handle basic tasks but are much slower for AI processing.
- Rendering Performance: GPU servers deliver much faster 3D rendering and video processing performance, whereas regular servers depend heavily on CPU resources.
- Parallel Computing: GPU dedicated servers excel at parallel computing, making them ideal for simulations, scientific workloads, and large-scale computations. Regular servers offer more limited parallel processing capabilities.
- Cost: GPU dedicated servers are more expensive due to specialized hardware, while regular dedicated servers are more budget-friendly for standard hosting needs.
GPU Dedicated Server Hosting FAQs
Here are the most common questions about GPU dedicated server hosting we get from our customers, Hence we elaborated our FAQ to ensure you find answers as quickly as possible.
The main benefits of dedicated server GPU include
- enhanced performance for AI and machine learning tasks.
- Energy efficiency and cost-effectiveness compared to traditional computing solutions.
- Scalability to handle increasing workloads without compromising performance.
Dedicated server with GPU has higher initial costs compared to standard servers. Also it requires expertise in GPU optimization for maximum efficiency.
We offer dedicated server with NVIDIA GPU, AMD Radeon Instinct™ Series, and customizable configurations based on your specific requirements.
Our support team assists in verifying software compatibility and provides guidance on optimization for GPU dedicated server hosting tasks.
Yes, we provide options for pre-installed software environments tailored for AI dedicated servers, machine learning frameworks, and scientific computing.
Our experts offer guidance and best practices for optimizing applications to leverage GPU acceleration effectively, ensuring maximum performance gains.
Consider your specific workload requirements, including computational intensity, data volume, and scalability needs, to select the ideal GPU configuration and server specifications.
Standard dedicated servers offer versatility but lack the optimized performance for AI and intensive computing tasks that dedicated server GPU provides. Choose based on your application’s demands for computing power and efficiency, and dedicated server pricing.
We accept a variety of payment methods for GPU servers, including credit cards, PayPal, and cryptocurrencies like Bitcoin. For more details on how to pay with crypto, please visit our pages on dedicated servers with crypto and dedicated servers with Bitcoin. We also support USDT dedicated server payments.
GPU hosting provides remote access to a high-performance server equipped with one or more GPUs. You deploy your workloads (AI, rendering, analytics, etc.) and leverage GPU acceleration for faster compute output.
CPUs handle sequential tasks efficiently, while GPUs are designed for parallel processing — making them significantly faster for machine learning, rendering, and large-scale calculations.
We support Linux Dedicated Server and Windows Dedicated Server environments. Custom OS installations are available on request.
Depending on configuration, servers may include AMD Ryzen™, Intel Xeon®, or EPYC processors to complement the GPU performance.
Most configurations are provisioned automatically and delivered within minutes. Custom builds may require additional setup time.
If you’re training AI models or rendering large files, an RTX 3090 / 4090 is ideal. For simulations or virtualization, AMD GPUs or multi-GPU setups may be more suitable.
Basic server management knowledge helps, but our support team can assist with OS setup, drivers, and initial configuration.
We provide data center-grade power redundancy, DDoS protection, high-speed connectivity, and 24/7 technical support across all GPU dedicated servers.
The best GPU dedicated server depends on workload size. RTX 4090 servers are ideal for small to mid-size AI training, while A100 and H100 servers are recommended for enterprise deep learning and large-scale machine learning tasks.
For small to mid-size machine learning workloads, RTX 4090 dedicated servers offer excellent price-to-performance. For large-scale training, A100 and H100 GPU dedicated servers are recommended.
GPU server pricing depends on the GPU, VRAM, CPU, RAM, storage, and bandwidth. High-end GPUs like the A100 and H100 cost more because they’re built for AI training and heavy compute workloads.
Yes. CUDA, TensorFlow, PyTorch, Docker, and related frameworks are supported.
GPU Dedicated Server Buying Guide: Specs, Setup, and Best Practices
A GPU dedicated server is only as powerful as the configuration behind it. Use the guide below to choose the right dedicated server with GPU for your workload, set it up correctly, and get consistent performance in production.
How to Choose the Right GPU Dedicated Server (Quick Checklist)
Use this checklist to select the best dedicated server GPU configuration:
- Workload type: training, inference, rendering, VDI, or gaming
- VRAM requirement: larger models and 4K/8K renders need more VRAM
- CPU support: data preprocessing and encoding can be CPU-heavy
- RAM capacity: avoid bottlenecks when feeding data to the GPU
- Storage: NVMe SSD for fast dataset loading and caching
- Network: low latency for remote workflows and real-time collaboration
- OS choice: Linux for ML stacks, Windows for certain VDI and tools
- Management level: managed vs unmanaged dedicated GPU hosting
Recommended Configurations by Use Case
Below are common dedicated GPU hosting scenarios and what typically matters most:
AI Training (Deep Learning)
- Prioritize: GPU VRAM, NVMe storage, RAM
- Best for: large datasets, transformer training, computer vision pipelines
AI Inference / Production Serving
- Prioritize: stable performance, network, reliability
- Best for: APIs, real-time inference, batch prediction
3D Rendering & Video Encoding
- Prioritize: GPU power, CPU cores, fast storage
- Best for: Blender, Unreal workflows, VFX, 4K/8K pipelines
VDI / Remote Workstations
- Prioritize: network latency, virtualization readiness, OS compatibility
- Best for: CAD, engineering, design teams, remote GPU desktops
Gaming & Game Servers
- Prioritize: CPU clock, latency, stability
- If your project needs gaming infrastructure, explore dedicated servers built for multiplayer hosting.
GPU Dedicated Server vs Cloud GPU Hosting
Dedicated GPU hosting gives you dedicated hardware and stable performance, while cloud GPU hosting is more flexible but usually shared.
For long-term AI projects, rendering, and enterprise workloads, bare metal GPU servers often deliver better value and performance.
Setup Guide (First 30 Minutes After Delivery)
Once your dedicated GPU server is provisioned, here’s a practical setup flow:
- Access Your Server via SSH or RDP : Use SSH for Linux GPU servers and Remote Desktop for Windows environments to connect securely after deployment.
- Install GPU Drivers and CUDA: Install NVIDIA drivers and CUDA packages required for GPU acceleration and framework compatibility.Example verification command: Nvidia-smi
- Verify GPU Health and Performance : Check GPU utilization, temperature, VRAM usage, and driver status using monitoring tools and GPU utilities.
- Install Frameworks and Monitoring Tools: Deploy AI frameworks, Docker containers, monitoring agents, and workload management tools based on project requirements.
- Secure the Server for Production: Configure firewall rules | Use SSH keys | Restrict public access | Enable monitoring | Keep drivers and frameworks updated
Performance Tips for GPU Dedicated Servers
- Avoid I/O and Memory Bottlenecks: Use NVMe SSD storage and adequate RAM allocation to prevent storage and memory limitations during GPU-intensive workloads.
- Optimize AI Training and Inference: Mixed precision training, optimized batch sizing, and proper dataloader configuration can significantly improve GPU utilization and training efficiency.
- Improve Rendering and Workstation Performance: Updated GPU drivers, balanced CPU performance, and thermal monitoring help maintain stable rendering and workstation performance under heavy workloads.
Security, Compliance, and Reliability
Our dedicated GPU servers are designed for production workloads where uptime and safety matter:
- Physical and network security at the data center level
- DDoS protection and stable routing for critical services
- Access control with root/admin permissions
- GDPR-aligned practices for data handling and privacy
Looking for the Best Deal on Dedicated GPU Servers?
If you’re flexible on hardware or want discounted inventory, check our limited deals and availability: Dedicated Server Outlet
GPU Performance Benchmarks and Recommendations
Performance results vary depending on workload type, framework optimization, cooling, software versions, and infrastructure configuration.
- Which GPU Is Best for AI : RTX 4090 servers are often suitable for startups and mid-scale AI projects, while A100 and H100 deployments are better for enterprise-scale model training.
- Which GPU Is Best for Rendering: RTX GPU servers provide excellent performance for Blender, Octane, Unreal Engine, and GPU rendering pipelines.
- When to Choose A100 or H100 Over RTX 4090: Choose A100 or H100 servers when workloads require enterprise scalability, larger memory environments, virtualization features, or advanced AI acceleration.
1Gbits Customer Reviews
The best proof of a great customer experience is your honest review. Want yours to appear here too? Go ahead and write one on the client's dashboard!
Elena SThe RTX 4090 dedicated server handled our PyTorch training workloads smoothly while giving us complete environment control and stable GPU performance.
Michael RWe moved our Blender rendering pipeline to dedicated GPU servers and significantly reduced render times for production projects.
