GPU Servers · Bare-metal AI & Compute
GPU Power Built for AI, Rendering & HPC
Dedicated NVIDIA Blackwell GPU nodes — bare-metal, no shared resources. Configure your exact memory, CPU, storage, and interconnect. Quote in hours.
- NVMe SSD storage — fast data pipelines
- 10 Gbps unmetered uplinks
- EU & US datacenter locations
- Quote within a few business hours
What can you run on a GPU server?
Bare-metal GPU nodes for every compute-intensive workload.
AI & LLM Training
Fine-tune large language models, train transformers, and run distributed workloads on multi-GPU nodes with NVLink or InfiniBand.
AI Inference
Serve LLMs and diffusion models at scale with low latency. High VRAM capacity means larger models fit in memory without quantization.
3D Rendering & VFX
GPU-accelerated Blender, Redshift, and V-Ray render nodes. Massive VRAM handles complex scenes without memory overflow.
Scientific HPC
CUDA-accelerated simulations, molecular dynamics, fluid dynamics, and numerical methods — with full bare-metal access.
Video Transcoding
NVENC hardware-accelerated encoding for high-volume video pipelines. Process 4K and 8K streams in real time.
Stable Diffusion & Image AI
Run Stable Diffusion, FLUX, or custom diffusion models at full precision — no shared GPU, no throttling, no queues.
Build Your GPU Configuration
Select your GPU, CPU, memory, and storage. We will review and send a tailored quote — no obligation.
What every GPU server includes
Bare-metal — no sharing
Every GPU core, every GB of VRAM is dedicated exclusively to your workload.
NVMe-backed data pipelines
Enterprise NVMe SSDs keep your training data pipeline from becoming the bottleneck.
10 Gbps unmetered
Move large model checkpoints and datasets fast — no egress surprises.
Quote within hours
Submit your config and our team responds with a tailored quote the same business day.
FAQ
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Yes — we support 1, 2, 4, and 8 GPU configurations. Multi-GPU nodes use NVLink (where supported) for GPU-to-GPU communication, critical for large model training.
Never. All GPU server nodes are bare-metal dedicated. You get 100% of the GPU cores, VRAM, and PCIe bandwidth — no hypervisor, no virtualisation overhead.
We pre-install the CUDA Toolkit, cuDNN, and can set up PyTorch, TensorFlow, or JAX environments. If you need a specific version or container runtime (Docker, Podman, Singularity), we accommodate that during provisioning.
Most GPU server configurations are provisioned within 24–72 hours of quote acceptance. Complex multi-GPU builds may take slightly longer. We will confirm a timeline in your quote.
Our GPU servers are monthly dedicated nodes, not hourly spot instances. This gives you consistent, uninterrupted access — no evictions, no capacity variability mid-training.
Yes. With bare-metal access you can install Docker, the NVIDIA Container Toolkit, and run any GPU-accelerated container or Kubernetes workload with full device passthrough.