- CPU
- Intel Core i9 13900K
- RAM
- 64GB DDR5
- Storage
- 2x 500GB NVMe M.2 SSD
- Uplink
- 2x 10G
GPU Dedicated ServersThe whole GPU,
The whole GPU,
not a time slice.
Shared GPU platforms hand you a slice of vRAM and a queue. These are single-tenant machines: the card, its memory and the full PCIe path belong to one workload. Nothing else is competing for it, and nothing throttles you at the hour mark.
Live availabilityRTX 4070 Tis235
GPU hardware in stock now.
Pulled from live rack inventory. If the card you need is not listed, we source it — custom GPU builds are routine work.
What people run on them
Where a dedicated GPU earns its keep.
AI inference & fine-tuning
24 GB of vRAM on a 4090 handles most open-weight models and LoRA fine-tuning without a cluster.
Rendering & VFX
Blender, Redshift and Octane finish in a fraction of CPU time, with no render-farm queue in front of you.
Batch & simulation
CUDA workloads that run for hours benefit from a card nobody else can preempt.
Video transcoding
NVENC turns large transcode backlogs into something that finishes overnight rather than over a week.
What a dedicated GPU server changes.
No shared vRAM, no noisy neighbours
On a shared GPU platform your model competes for video memory and PCIe bandwidth with whatever else landed on the card. Batch sizes get capped by what is free rather than what the card can hold, and throughput swings with other tenants. A dedicated card removes that variable entirely: 24 GB is yours, the bus is yours, and a benchmark you run today means something tomorrow.
Predictable cost for sustained work
Hourly GPU rental is excellent for bursts and expensive for anything continuous. Once a card is busy more than a few hours a day, a fixed monthly bare-metal price is usually the cheaper answer — and it comes without egress metering, without preemption, and without losing your environment when the instance goes away.
Good to know
GPU server FAQ.
Which GPUs are available?
Current stock is shown live on this page — today that centres on NVIDIA RTX 4090 configurations. Other cards, including professional and data-centre GPUs, can be sourced on request; tell us the workload and we will quote the right card.
Is the GPU shared with anyone?
No. These are single-tenant bare-metal servers. The card, its vRAM and the PCIe path belong to your machine alone — there is no virtualisation layer and no other tenant scheduled on it.
Can I install CUDA and my own drivers?
Yes. You get full root access, so you install whatever driver, CUDA version, container runtime or framework your stack needs. We can pre-install a base image with drivers if you prefer to start from there.
Is it cheaper than hourly cloud GPU?
For sustained use, almost always. Hourly rental wins for short bursts; once the card is busy several hours a day a fixed monthly price usually costs less, and there is no egress metering on top.
Where are the GPU servers hosted?
In our European data centres in Frankfurt and the Netherlands, on our own network. Your data and your models stay inside the EU under GDPR.
Custom configurations
Need something we don't list?
Larger disks, a different CPU, more RAM, a specific storage layout — almost anything is possible. Tell us what the workload actually needs and we will prepare an individual offer.
Tell us the workload and budget — most quotes come back within one business day. Green ITFor more green IT,
For more green IT,
in every rack we run.
The carbon footprint of the internet — its servers, its data centres — keeps growing. Efficient hardware is part of the answer, but only part. Every Hostigan server runs on 100% green electricity, in every data centre we operate. And we do one thing more.
- 100% green electricityEvery server in every one of our data centres runs on electricity from renewable sources. Not offset after the fact — sourced that way.
- Hardware chosen for efficiencyModern platforms and efficient cooling do the same work for less power. The greenest watt is the one never drawn in the first place.
- Two trees for every ratingEvery review we receive has two new trees planted — whichever way the review goes.