NVIDIA GPU Dedicated ServersTesla T4, A2, A10 & L4 — Built for AI, Rendering & HPC
Rent a bare-metal dedicated server with an exclusive NVIDIA GPU — no shared tenancy, no noisy neighbors. Run AI training, LLM inference, 3D rendering, and video encoding on dual-Xeon hardware with full root/administrator access, hosted in our UK (London) data center.
Choose Your GPU Configuration
Bare-metal dual-Xeon servers with a dedicated NVIDIA GPU, full root access, and 100 TB bandwidth included.
NVIDIA Tesla T4
- Tesla T4 · 16 GB GDDR6
- 64 GB DDR4 ECC RAM
- 2× 960 GB SSD · RAID 1
- 1 Gbps Port · 100 TB Bandwidth
- Full Root / Admin · UK Data Center
NVIDIA A2
- A2 Tensor Core · 16 GB GDDR6
- 64 GB DDR4 ECC RAM
- 2× 960 GB SSD · RAID 1
- 1 Gbps Port · 100 TB Bandwidth
- Full Root / Admin · UK Data Center
2× NVIDIA Tesla T4
- 2× Tesla T4 · 16 GB GDDR6 each
- 64 GB DDR4 ECC RAM
- 2× 960 GB SSD · RAID 1
- 1 Gbps Port · 100 TB Bandwidth
- Full Root / Admin · UK Data Center
NVIDIA A10
- A10 Ampere · 24 GB GDDR6
- 64 GB DDR4 ECC RAM
- 2× 960 GB SSD · RAID 1
- 1 Gbps Port · 100 TB Bandwidth
- Full Root / Admin · UK Data Center
NVIDIA L4
- L4 Ada Lovelace · 24 GB GDDR6
- 64 GB DDR4 ECC RAM
- 2× 960 GB SSD · RAID 1
- 1 Gbps Port · 100 TB Bandwidth
- Full Root / Admin · UK Data Center
2× NVIDIA L4
- 2× L4 Ada Lovelace · 24 GB each
- 128 GB DDR4 ECC RAM
- 2× 960 GB SSD · RAID 1
- 10 Gbps Port · 100 TB Bandwidth
- Full Root / Admin · UK Data Center
4× NVIDIA L4
- 4× L4 Ada Lovelace · 24 GB each
- 128 GB DDR4 ECC RAM
- 2× 960 GB SSD · RAID 1
- 10 Gbps Port · 100 TB Bandwidth
- Full Root / Admin · UK Data Center
GPU Spec Comparison
Real specs for every GPU we offer — pick by workload, not guesswork.
| GPU | VRAM | CUDA Cores | Tensor Cores | Architecture | FP32 Perf. | Best For |
|---|---|---|---|---|---|---|
| Tesla T4 | 16 GB GDDR6 | 2,560 | 320 | Turing | 8.1 TFLOPS | Cost-efficient inference, batch jobs |
| NVIDIA A2 | 16 GB GDDR6 | 1,280 | 40 | Ampere | 4.5 TFLOPS | Low-power inference, entry AI |
| NVIDIA A10 | 24 GB GDDR6 | 9,216 | 288 | Ampere | 31.2 TFLOPS | AI training, graphics, workstations |
| NVIDIA L4 | 24 GB GDDR6 | 7,424 | 240 | Ada Lovelace | 30.3 TFLOPS | Efficient inference, video encoding |
What Is a GPU Dedicated Server?
A GPU dedicated server is a physical, single-tenant machine with an exclusive NVIDIA GPU alongside its own CPU and RAM — no virtualization overhead, no other customer sharing the hardware. That exclusivity is what makes it different from a shared GPU cloud instance: the entire card, and all of its VRAM and CUDA cores, is available to your workload alone.
Whether you're training or fine-tuning a model, serving LLM inference at scale, rendering 3D scenes in Blender or Octane, or transcoding video with hardware-accelerated NVENC, a dedicated GPU removes the "noisy neighbor" slowdowns you get on shared infrastructure. Combined with full root or administrator access, you control every driver, CUDA version, and framework exactly as you would on your own hardware.
Built For These Workloads
Match the GPU to the job — not the other way around
AI Model Training
Goal: Fine-tune or train neural networks from scratch.
Power: A10 or multi-GPU L4 with up to 128GB RAM.
LLM Inference & Serving
Goal: Run Llama, Mistral, or DeepSeek with Ollama/vLLM.
Power: T4 or L4 balance throughput with cost.
3D Rendering & VFX
Goal: Render scenes in Blender, V-Ray, or Octane.
Power: A10 or L4 CUDA cores cut render times.
Video Encoding & Streaming
Goal: Transcode or live-stream with hardware encoding.
Power: L4's NVENC/AV1 engine for Plex, OBS, FFmpeg.
Data Science & HPC
Goal: Parallelize simulations and statistical models.
Power: GPU + up to 64 dual-Xeon threads.
Virtual GPU Workstations
Goal: Remote CAD, graphics, or engineering workstation.
Power: Full admin/root access on any GPU tier.
Server Features
Full Root / Admin Access
Install any OS, driver, or framework — total control of the hardware.
Enterprise SSD Storage
Dual 960GB SSDs in RAID 1 for redundancy and consistent I/O.
Up to 10 Gbps Networking
Multi-GPU plans ship with 10 Gbps uplinks for faster data transfer.
100 TB Bandwidth Included
Generous monthly transfer allowance on every plan — no surprise overages.
DDoS Protection
Standard network-level protection included on all UK data center servers.
24/7 Expert Support
Real engineers on call for setup, driver, and CUDA/framework help.
Other Dedicated & RDP Options
10GBPS Dedicated Server
Unmetered bandwidth on a 10GBPS backbone, NVMe SSD, Windows Server.
AMD EPYC Storage RDP
Hybrid NVMe + HDD storage, up to 10TB, AMD EPYC 7402P.
Windows RDP Server
Full admin access, dedicated Intel i7/AMD Ryzen, USA or Finland.
Related Reading
Frequently Asked Questions
Expert answers about NVIDIA GPU dedicated hosting.
What is a GPU dedicated server? +
A GPU dedicated server is a physical, single-tenant server with an exclusive NVIDIA GPU alongside its CPU and RAM — no virtualization overhead and no other customer sharing your hardware. Every plan here ships on dual-Xeon platforms with a dedicated Tesla T4, A2, A10, or L4 GPU, giving you consistent, predictable performance for AI, rendering, and compute-heavy workloads.
Do I need a GPU for my dedicated server? +
You need a GPU if your workload relies on parallel processing — AI model training or inference, LLM serving, 3D rendering, video transcoding, or scientific computing. A standard CPU-only dedicated server is fine for web hosting, databases, or general application workloads; add a GPU only when your software specifically benefits from CUDA acceleration.
Which GPU should I choose — Tesla T4, A2, A10, or L4? +
Pick the T4 or A2 (16GB) for cost-efficient AI inference and light workloads. Pick the A10 (24GB, Ampere) for a balance of training performance and graphics work. Pick the L4 (24GB, Ada Lovelace) for the most power-efficient inference and hardware video encoding. Need to run larger models or parallelize training? Step up to the 2x or 4x L4 configurations.
Can these servers run AI model training and LLM inference? +
Yes. Every GPU here supports CUDA and cuDNN, so frameworks like PyTorch, TensorFlow, and Hugging Face Transformers run natively. The A10 and multi-GPU L4 plans are well suited to fine-tuning and training; the T4, A2, and single L4 plans are optimized for cost-efficient inference and serving models with Ollama or vLLM.
What's the difference between a single-GPU and multi-GPU (2x/4x L4) plan? +
Multi-GPU plans let you split larger models across GPUs, run more concurrent inference streams, or parallelize training jobs. They also come with 128GB RAM and a 10 Gbps network port instead of 1 Gbps, so data loading and multi-GPU communication aren't the bottleneck.
Do I get full root or administrator access? +
Yes — every plan includes full Administrator access on Windows or root access on Linux. You can install any driver, CUDA toolkit version, container runtime, or framework exactly as you would on your own physical hardware.
What operating systems can I install? +
We support Windows Server (2016, 2019, 2022) and Windows 10/11 Pro, plus Linux distributions including Ubuntu, CentOS, Debian, and AlmaLinux — all with NVIDIA drivers ready to configure.
Where are these servers hosted? +
All NVIDIA GPU dedicated servers are hosted in our UK data center in London, giving low-latency connectivity across the UK and mainland Europe.
What's the network speed and bandwidth limit? +
Single-GPU plans (T4, A2, A10, L4) include a 1 Gbps port; the 2x and 4x L4 multi-GPU plans include a 10 Gbps port. Every plan includes 100 TB of monthly bandwidth.
How long does deployment take? +
Since these are physical dedicated servers, initial provisioning typically takes 12 to 24 hours depending on the configuration and OS requested. You'll receive login credentials by email as soon as the server is active.
Is DDoS protection included? +
Yes, our UK data center includes standard DDoS protection on every server to mitigate common network-level attacks and keep your workloads online.
How do I access my GPU server? +
Windows servers are accessed via Remote Desktop Protocol (RDP), built into every Windows machine. Linux servers are accessed via SSH using a terminal or a client like PuTTY.
Ready to Power Up?
Get your dedicated NVIDIA GPU server deployed today.