Dedicated GPU servers from £69/mo

Run AI Models 24/7 on Dedicated UK GPU Servers

No shared resources. No hourly billing. No GPU contention. Deploy a bare metal server with a dedicated NVIDIA, AMD, or Intel GPU — your hardware, your rules.

No noisy neighbours Fixed monthly pricing Full root access Deployed in <24 hours

Compare GPU Servers Talk to Sales

Entry-Level

RTX 3050

from /mo

6 GB GDDR6 VRAM

Choose Your GPU Server

12 GPUs across four tiers. Pick the VRAM and compute you need — every server includes a Ryzen CPU, up to 128 GB RAM, NVMe storage, and 1 Gbps connectivity.

Entry-Level Mid-Range High-Performance Flagship

Entry-Level GPUs

Best for: Android emulators, light inference, Stable Diffusion, dev & testing, smaller LLMs up to 8B

NVIDIA RTX 3050

Ideal for: Android emulators, light CUDA dev, small model inference

ArchitectureAmpere

CUDA Cores2,304

Boost Clock1,470 MHz

FP326.8 TFLOPS

Bandwidth168.0 GB/s

BusPCIe 4.0 x8

6 GB GDDR6 VRAM

Starting at /mo Start Deployment

NVIDIA RTX 5060 BLACKWELL

Ideal for: Stable Diffusion XL, Mistral 7B, real-time encoding, Blender

ArchitectureBlackwell 2.0

CUDA Cores3,840

Boost Clock2,497 MHz

FP3219.2 TFLOPS

Bandwidth448.0 GB/s

BusPCIe 5.0 x8

8 GB GDDR7 VRAM

Starting at /mo Start Deployment

NVIDIA RTX 5060 Ti 16 GB

Ideal for: LLaMA 8B, Flux, SDXL, ComfyUI workflows, YOLO inference

ArchitectureBlackwell 2.0

CUDA Cores4,608

Boost Clock2,572 MHz

FP3223.7 TFLOPS

Bandwidth448.0 GB/s

BusPCIe 5.0 x8

16 GB GDDR7 VRAM

Starting at /mo Start Deployment

Mid-Range GPUs

Best for: LLaMA 8B–13B, Flux, ComfyUI, ROCm/OneAPI dev, AV1 encoding, professional rendering

AMD RX 9070 XT RDNA 4

Ideal for: ROCm workloads, Blender, DaVinci Resolve, multi-emulator setups

ArchitectureRDNA 4.0

Cores4,096

Boost Clock2,970 MHz

FP3248.7 TFLOPS

Bandwidth644.6 GB/s

BusPCIe 5.0 x16

16 GB GDDR6 VRAM

Starting at /mo Start Deployment

NVIDIA RTX 3090 POPULAR

Ideal for: LLaMA 13B, DeepSeek, Mistral, Stable Diffusion, 24/7 inference APIs

ArchitectureAmpere

CUDA Cores10,496

Boost Clock1,695 MHz

FP3235.6 TFLOPS

Bandwidth936.2 GB/s

BusPCIe 4.0 x16

24 GB GDDR6X VRAM

Starting at /mo Start Deployment

Intel Arc Pro B70 NEW

Ideal for: OpenCL workloads, AV1 encoding, OneAPI development, ISV-certified apps

ArchitectureXe2

Cores4,096

Boost ClockTBA

FP3222.9 TFLOPS

Bandwidth608 GB/s

BusPCIe 5.0 x16

32 GB GDDR6 VRAM

Starting at /mo Start Deployment

High-Performance GPUs

Best for: LLaMA 30B+, vLLM production, large batch training, multi-stream NVENC, professional 3D/CAD

NVIDIA RTX 5080 BLACKWELL

Ideal for: vLLM inference, large batch training, Flux Pro, multi-stream NVENC

ArchitectureBlackwell 2.0

CUDA Cores10,752

Boost Clock2,617 MHz

FP3256.3 TFLOPS

Bandwidth960.0 GB/s

BusPCIe 5.0 x16

16 GB GDDR7 VRAM

Starting at /mo Start Deployment

AMD Radeon AI Pro R9700 AI PRO

Ideal for: ROCm AI training, PyTorch on AMD, ISV-certified CAD/3D rendering

ArchitectureRDNA 4

Shading Units4,096

Boost Clock2,920 MHz

FP3247.8 TFLOPS

Bandwidth644.6 GB/s

BusPCIe 5.0 x16

32 GB GDDR6 VRAM

Starting at /mo Start Deployment

NVIDIA RTX 4090 24 GB

Ideal for: LLaMA 30B, full fine-tuning, vLLM production, 4K rendering, AI training

ArchitectureAda Lovelace

CUDA Cores16,384

Boost Clock2,520 MHz

FP3282.6 TFLOPS

Bandwidth1,008 GB/s

BusPCIe 4.0 x16

24 GB GDDR6X VRAM

Starting at /mo Start Deployment

Flagship & Workstation GPUs

Best for: LLaMA 70B, full-precision training, enterprise AI, massive datasets, 8K rendering

AMD Ryzen AI MAX+ 395 96 GB

Ideal for: LLaMA 70B unquantised, massive unified memory workloads, research

ArchitectureStrix Halo

TOPS126

Boost Clock5.1 GHz

FP3214.8 TFLOPS

Bandwidth256.0 GB/s

BusPCIe 4.0

96 GB LPDDR5X Unified Memory

Starting at /mo Start Deployment

NVIDIA RTX 5090 FLAGSHIP

Ideal for: LLaMA 70B quantised, full fine-tuning, vLLM production, 4K+ rendering

ArchitectureBlackwell 2.0

CUDA Cores21,760

Boost Clock2,407 MHz

FP32104.8 TFLOPS

Bandwidth1.79 TB/s

BusPCIe 5.0 x16

32 GB GDDR7 VRAM

Starting at /mo Start Deployment

NVIDIA RTX 6000 PRO WORKSTATION

Ideal for: Enterprise AI training, LLaMA 70B+ full precision, 8K compositing, HPC

ArchitectureBlackwell 2.0

CUDA Cores24,064

Boost Clock2,617 MHz

FP32126.0 TFLOPS

Bandwidth1.79 TB/s

BusPCIe 5.0 x16

96 GB GDDR7 VRAM

Starting at /mo Start Deployment

Why Dedicated Beats Cloud GPU

Cloud GPU billing adds up fast. Shared instances throttle your workloads. Here’s why teams switch to GigaGPU.

Cloud GPU (RunPod, Vast, AWS)

Hourly billing — costs spike on long-running jobs

Shared hardware — noisy neighbours kill performance

GPU availability lottery — instances vanish mid-job

No root access or custom driver stacks

Data leaves your control on shared infra

GigaGPU Dedicated

Fixed monthly price — no billing surprises

Bare metal isolation — entire machine is yours

Always-on GPU — no preemption, no waitlists

Full root access — any OS, driver, framework

UK data residency — your data stays in the UK

Running a model 24/7 on cloud GPU? You’re probably overpaying by 3–5x.

Purpose-Built for These Workloads

Not generic compute. These are the specific tools and models our customers run every day.

Self-Host LLMs

Run open-source language models 24/7 with full CUDA support and no per-token API costs. Serve your own inference endpoints with vLLM or Ollama.

LLaMA 3 DeepSeek Mistral Qwen Phi

Generate Images & Video

Run generative AI models locally for image creation, upscaling, and video generation. Full control over your pipeline, no external API dependencies.

Stable Diffusion Flux ComfyUI WAN-AI

Speech & Audio AI

Deploy speech-to-text, text-to-speech, and audio processing models. Build voice agents, transcription pipelines, and real-time audio tools.

Whisper Bark Coqui TTS Kokoro XTTS-v2

Computer Vision & OCR

Run object detection, image classification, and document processing at scale. Process thousands of images without API rate limits or per-call fees.

YOLO PaddleOCR SAM CLIP

Gaming & Streaming

Host cloud gaming instances, run pixel-streaming setups, or power GPU-accelerated game servers with low-latency UK connectivity.

Parsec Sunshine NVENC Moonlight

Rendering & 3D Production

Accelerate GPU-powered rendering, video encoding, and architectural visualisation. Full OpenGL and Vulkan support for professional workflows.

Blender DaVinci Resolve FFmpeg Unreal Engine

What You Get with Every Server

No hidden fees. No surprise add-ons. Every dedicated GPU server ships fully loaded.

Bare Metal Isolation

No virtualisation, no shared resources. The entire physical machine — CPU, RAM, GPU, storage — is yours alone. Zero noisy neighbours.

Full Root Access

Install any OS, driver stack, or framework. Run Docker, Kubernetes, or bare-metal CUDA. No permission requests, no support tickets.

UK Data Residency

Your data stays in the UK on hardware you control. Redundant power, cooling, and networking with 99.9% uptime SLA.

1Gbps Network Port

NVMe SSD Storage

128GB DDR4/DDR5 RAM

Ryzen CPU

DDoS Protection

24/7 Monitoring

IPv4 & IPv6

Remote Reboot

Expert GPU Support

Any Operating System

Deploy in Three Steps

Go from zero to a running GPU server in under 24 hours. No sales calls required.

Pick Your GPU

Choose from 12 GPUs across four performance tiers. Match the VRAM and compute to your workload.

Configure & Order

Select your OS, storage, and billing cycle. We handle provisioning, networking, and driver setup.

Start Building

SSH in, install your stack, deploy your models. Root access, full GPU passthrough, 1Gbps — ready to go.

Frequently Asked Questions

What is dedicated GPU hosting?

Dedicated GPU hosting gives you an entire physical server with a dedicated graphics card. Unlike cloud GPU instances that share hardware between tenants, you get full bare-metal access to the GPU, CPU, RAM, and storage — consistent performance, no noisy neighbours, no preemption.

How much VRAM do I need?

For small model inference (Whisper, Phi, YOLO): 8–16 GB. For mid-size models (LLaMA 13B, Stable Diffusion XL): 16–24 GB. For large models (LLaMA 70B, full-precision training): 32–96 GB. Not sure? Contact sales and we’ll recommend the right GPU for your workload.

How is this different from cloud GPU?

Cloud GPU (RunPod, Vast, AWS) bills per hour, shares hardware, and can preempt your instance mid-job. GigaGPU gives you a dedicated physical server at a fixed monthly price — the GPU is always available, always yours, and performance never varies.

Can I customise the server?

Yes. Contact sales for custom CPU, RAM, storage, or GPU configurations. We can also migrate you to a higher-tier server as your workload grows, with minimal downtime.

How quickly are servers deployed?

Most servers deploy within 24 hours. Custom configurations or high-demand GPUs may take slightly longer. We’ll keep you updated throughout.

Which OS can I install?

Any Linux distribution (Ubuntu, Debian, CentOS, Rocky Linux) or Windows Server. Full root access — install whatever you need.

Do you support Docker and Kubernetes?

Yes. Full root access means Docker, Kubernetes, Docker Compose, or any container platform. NVIDIA Container Toolkit is fully supported for GPU passthrough to containers.

Do your servers support CUDA?

All NVIDIA GPUs support CUDA, cuDNN, and TensorRT. Install PyTorch, TensorFlow, JAX, or any CUDA-accelerated framework. AMD GPUs support ROCm and OpenCL.

Can I use it for gaming or streaming?

Yes. Our servers run cloud gaming platforms, pixel-streaming setups (Parsec, Sunshine), and GPU-accelerated game servers. Full root access with dedicated GPU means smooth, low-latency performance.

What bandwidth is included?

Every server includes a 1Gbps port with generous monthly allowances — enough for API serving, remote desktop, dataset transfers, and model deployment. Need more? Contact sales for custom networking.

Stop Renting GPU Time. Own Your Compute.

Fixed monthly pricing. Dedicated hardware. No surprises. Deploy your first server today.

Compare GPU Servers Talk to Sales

Run AI Models 24/7 on Dedicated UK GPU Servers

Choose Your GPU Server

Entry-Level GPUs

Mid-Range GPUs

High-Performance GPUs

Flagship & Workstation GPUs

Why Dedicated Beats Cloud GPU

Cloud GPU (RunPod, Vast, AWS)

GigaGPU Dedicated

Purpose-Built for These Workloads

Self-Host LLMs

Generate Images & Video

Speech & Audio AI

Computer Vision & OCR

Gaming & Streaming

Rendering & 3D Production

What You Get with Every Server

Bare Metal Isolation

Full Root Access

UK Data Residency

Deploy in Three Steps

Pick Your GPU

Configure & Order

Start Building

Frequently Asked Questions

Stop Renting GPU Time. Own Your Compute.

Have a question? Need help? Contact us

Have a question? Need help?