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Enterprise GPU Hosting

GPU Servers.
Choose Your Card.

NVIDIA RTX PRO Blackwell workstation GPUs and RTX 5090 - select the perfect card for your workload. Professional certified drivers, full root access, and dedicated hardware.

Blackwell Architecture
Up to 96GB GDDR7
Multi-GPU Options
Pro Certified Drivers
Configure GPU Server
Instant deployment available
Select GPU
Available GPUs Click to configure
RTX PRO 2000
16GB GDDR7
Dev/Test
RTX PRO 4000
24GB GDDR7
Inference
Popular
RTX PRO 6000
96GB GDDR7
LLM Training
RTX 5090
32GB GDDR7
AI/Inference
Blackwell
Architecture
GDDR7
Memory
Pro
Certified

Configure Your GPU Server

Select your GPU and specifications below. Our team will respond with a detailed quote within 24 hours.

Free consultation
No commitment
Free consultation • Response within 24h
or
Need a custom dedicated server?
Build Custom Server CPU-focused configurations
GPU-Accelerated Computing

Why GPU Servers
Change Everything

CPUs are sequential. GPUs are massively parallel. For AI workloads, that's the difference between days and minutes.

100×
Faster than CPU-only
for matrix operations
01

Tensor Cores

Purpose-built for AI. Matrix operations that would take hours on CPUs complete in seconds with dedicated tensor hardware.

02

Massive Parallelism

Thousands of CUDA cores working simultaneously. Train models, render frames, or encode video in a fraction of the time.

03

High-Bandwidth Memory

GDDR7 delivers over 1TB/s bandwidth. Large models fit entirely in VRAM - no slow system memory swapping.

04

CUDA Ecosystem

PyTorch, TensorFlow, CUDA, cuDNN - the entire ML stack is optimized for NVIDIA. Full compatibility guaranteed.

GPU Server Applications

Built for Compute-Intensive
Workloads

From training neural networks to rendering photorealistic imagery, GPU dedicated servers handle the workloads that would take CPUs weeks to complete. Explore our full range of AI & GPU solutions.

Most Popular RTX PRO 6000
AI and machine learning training

AI & Machine Learning Training

Train large language models, computer vision networks, and recommendation systems. The RTX PRO 6000's 96GB GDDR7 handles models that won't fit in consumer GPUs. Fine-tune LLMs like Llama, Mistral, or your custom architectures without memory constraints.

PyTorch TensorFlow JAX Hugging Face CUDA
Recommended RTX PRO 6000 / 4000
VRAM Needed 24GB–96GB
High Demand RTX 5090
AI inference at scale

AI Inference at Scale

Deploy trained models for production inference. Serve thousands of requests per second with low latency. The RTX 5090 delivers exceptional price-to-performance for inference workloads, making it ideal for chatbots, image generation APIs, and real-time AI services. For lighter inference tasks, a high-performance VPS may also be suitable.

TensorRT Triton vLLM Ollama FastAPI
Recommended RTX 5090 / PRO 4000
VRAM Needed 16GB–32GB
3D rendering

3D Rendering & CGI

Blender Cycles, OctaneRender, Redshift, V-Ray GPU. Render complex scenes with ray tracing in minutes instead of hours. Animation studios use GPU farms to meet deadlines.

Blender OctaneRender V-Ray
Video encoding

Video Encoding & Transcoding

NVENC hardware encoding for H.264, H.265, and AV1. Transcode 4K streams in real-time. Build your own video platform with GPU-accelerated FFmpeg pipelines.

FFmpeg NVENC HandBrake
Scientific computing

Scientific Computing

Molecular dynamics, climate modeling, physics simulations. CUDA-accelerated libraries like cuBLAS and cuFFT make GPUs essential for research.

GROMACS AMBER NAMD
Generative AI

Generative AI & Diffusion

Run Stable Diffusion, DALL-E, Midjourney alternatives locally. Generate images, videos, and audio with complete privacy and no API costs.

ComfyUI A1111 Flux
Blackwell GPU
Blackwell Architecture Latest NVIDIA GPUs
GDDR7 memory
Up to 96GB VRAM GDDR7 Memory
10Gbps network
10Gbps Network Redundant Uplinks
Tbps mitigation
Tbps+ Mitigation Enterprise Security

Available GPU Models

Professional and consumer Blackwell GPUs for every workload size.

GPU Model
VRAM
Best For
Tier
RTX PRO 6000
96GB GDDR7
LLM Training, Large Models
Pro
RTX PRO 4000
24GB GDDR7
Inference, Training
Pro
RTX PRO 2000
16GB GDDR7
Dev/Test, Small Models
Pro
RTX 5090
32GB GDDR7
Inference, Rendering
Consumer
Pro GPUs include certified drivers, ECC memory support, and enterprise warranty
Server Platform

Enterprise Foundation

Every GPU server is built on server-grade hardware in our ISO certified data centers, designed for 24/7 operation.

CPU
Intel Xeon / AMD EPYC Server-grade CPUs
ECC memory
Up to 512GB DDR5 ECC Error-correcting memory
NVMe storage
NVMe SSD Storage High-IOPS, low latency
IPMI access
Full IPMI/BMC Access Remote KVM & power control
Supported OS:
Ubuntu Debian Rocky Windows
GPU Server Locations

Deploy close to your users

GPU servers available in our European data centers

Sofia, Bulgaria

Sofia

Bulgaria • East EU
Datacenter Telepoint DC
Test IP 79.124.7.8
Nuremberg, Germany

Nuremberg

Germany • Central EU
Datacenter Hetzner DC
Test IP 194.35.12.68

GPU availability varies by location

Contact us for current GPU stock →
FAQ

Common
Questions

Everything you need to know about GPU dedicated servers for AI, ML, and rendering.

Contact Sales

For LLM training and large models, choose the RTX PRO 6000 with 96GB GDDR7 - it handles models that won't fit in consumer GPUs. For inference and medium-sized training, the RTX PRO 4000 (24GB) or RTX 5090 (32GB) offer excellent performance. The RTX PRO 2000 (16GB) is ideal for dev/test.

RTX PRO series GPUs include NVIDIA certified drivers (ISV certifications), optional ECC memory support, enterprise warranty, and are designed for 24/7 operation. Consumer GPUs like the RTX 5090 offer exceptional raw performance at lower price points but with standard warranty and drivers.

Yes, we offer multi-GPU configurations. Server chassis and motherboard selection depends on your requirements - some platforms support 2, 4, or even 8 GPUs. For large-scale deployments, explore our bare metal clusters. Contact our team to discuss your specific workload and we'll recommend the optimal configuration.

We can pre-install NVIDIA drivers, CUDA toolkit, and cuDNN upon request - see our managed services for full setup assistance. Alternatively, you receive a clean OS installation with root access to configure your preferred ML stack. Ubuntu is the most popular choice for GPU servers due to best driver compatibility.

In-stock configurations typically ship within 24-72 hours. Custom builds or specific GPU models may take 1-2 weeks. Contact sales for current availability and lead times - we maintain stock of popular configurations.

All major operating systems support NVIDIA GPUs: Ubuntu (most popular for ML), Debian, Rocky Linux, CentOS Stream, and Windows Server. We recommend Ubuntu 22.04 or 24.04 LTS for AI/ML workloads due to best framework compatibility.

Ready to Accelerate?

GPU Compute Power
Without the Cloud Markup

Dedicated GPU servers at a fraction of cloud GPU prices. No per-hour billing surprises - flat monthly rates for predictable AI infrastructure costs.

Configure Your GPU Server
Free consultation No commitment quote Expert guidance