Rent dedicated and virtual GPU servers for AI training, fine-tuning and inference. Choose NVIDIA or AMD GPUs by VRAM and workload, with hourly or monthly billing, NVMe storage, high-speed networking and pre-installed AI tools on supported configurations.
If you are looking for VPS with GPU, find out our instant virtual servers RTX A5000 / RTX A4000 GPU cards.
Compare AI GPU server configurations by GPU model and VRAM, GPU count, CPU, RAM, NVMe storage, network, location, availability and current pricing. Choose hourly or monthly billing plans on supported servers, or configure a custom GPU server for your AI workload. Hourly and monthly billing are available on supported configurations. Current prices and availability are shown directly in the live server catalog.
The selected collocation region is applied for all components below
The right GPU depends on your model size, precision, VRAM requirements, training or inference workload, and whether you need one GPU or a multi-GPU configuration. Use the table below as a starting point, then compare the current server configurations and availability in the HOSTKEY catalog.
|
GPU Model |
VRAM |
Best For |
Training Fit |
Inference Fit |
Notes / CTA |
|---|---|---|---|---|---|
|
NVIDIA H100 |
80 GB |
Large-model training, fine-tuning and high-throughput inference |
Very high |
Very high |
Use multi-GPU/interconnect claims only where supported |
|
NVIDIA A100 |
80 GB |
Training, fine-tuning and production inference |
High |
High |
Confirm current inventory / interconnect |
|
RTX PRO 6000 |
96 GB |
High-VRAM single-GPU fine-tuning, inference and visual AI |
High |
Very high |
Confirm exact current model/inventory |
|
RTX A6000 |
48 GB |
Fine-tuning, computer vision and AI research |
Medium–High |
High |
Use current availability |
|
RTX 5090 |
32 GB |
Development, inference, image generation and smaller training jobs |
Medium |
High |
Consumer/prosumer class |
|
RTX 4090 |
24 GB |
Prototyping, inference, image generation and smaller AI workloads |
Medium |
High |
24 GB VRAM |
|
AMD Radeon AI PRO R9700 |
32 GB |
AMD AI/compute workloads where software stack is supported |
Medium |
Medium |
Confirm ROCm/toolchain compatibility |
Start with a clean operating system or use supported pre-installed environments for AI, machine learning and data workloads. Available tools may include PyTorch, TensorFlow, JupyterLab, Anaconda, Apache Spark and Apache Airflow. Explore AI Platform and Pre-installed Apps
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Address:
W. Frederik Hermansstraat 91, 1011 DG, Amsterdam, The Netherlands
Order: hostkey.com
Address:
W. Frederik Hermansstraat 91, 1011 DG, Amsterdam, The Netherlands
Order: hostkey.com
Rent instant server with RTX 5090 GPU in 15 minutes!
There is no single best GPU for every AI workload. For larger training jobs, high-VRAM data-center GPUs such as H100 or A100 may be appropriate; smaller models and development workloads can often run on RTX or professional GPUs. Compare model size, precision, VRAM, GPU count and budget before choosing.
VRAM requirements depend on model size, precision, batch size, context length and whether you are training, fine-tuning or running inference. Start with the model’s memory requirement and leave headroom for activations, KV cache and runtime overhead.
Training usually needs more memory and sustained compute, especially for larger models and multi-GPU workloads. Inference may prioritize latency, throughput and cost per request. The best GPU can therefore differ between the two stages.
Yes, HOSTKEY offers multi-GPU configurations. The number of GPUs and available interconnect options depend on the server and accelerator model.
Yes, users with administrative access can install their own software stack. Supported configurations can also be deployed with pre-installed tools such as PyTorch, TensorFlow and JupyterLab.
Hourly and monthly billing are available on supported configurations. Current billing options, prices and availability are shown in the live server catalog.
Ready configurations can be available from 15 minutes. Custom hardware requires additional provisioning time depending on components and location.
A dedicated GPU server provides the full physical server environment and broader customization options. A GPU VPS can be suitable when a virtualized environment is enough.
| Location | Server type | GPU | Processor Specs | System RAM | Local Storage | Monthly Pricing | 6-Month Pricing | Annual Pricing | |
|---|---|---|---|---|---|---|---|---|---|
| NL | Dedicated | 1 x GTX 1080Ti | Xeon E-2288G 3.7GHz (8 cores) | 32 Gb | 1Tb NVMe SSD | €170 | €160 | €150 | |
| NL | Dedicated | 1 x RTX 3090 | AMD Ryzen 9 5950X 3.4GHz (16 cores) | 128 Gb | 480Gb SSD | €384 | €327 | €338 | |
| RU | VDS | 1 x GTX 1080 | 2.6GHz (4 cores) | 16 Gb | 240Gb SSD | €92 | €86 | €81 | |
| NL | Dedicated | 1 x GTX 1080Ti | 3.5GHz (4 cores) | 16 Gb | 240Gb SSD | VDS | €94 | €88 | €83 |
| RU | Dedicated | 1 x GTX 1080 | Xeon E3-1230v5 3.4GHz (4 cores) | 16 Gb | 240Gb SSD | €119 | €112 | €105 | |
| RU | Dedicated | 2 x GTX 1080 | Xeon E5-1630v4 3.7GHz (4 cores) | 32 Gb | 480Gb SSD | €218 | €205 | €192 | |
| RU | Dedicated | 1 x RTX 3080 | AMD Ryzen 9 3900X 3.8GHz (12 cores) | 32 Gb | 480Gb NVMe SSD | €273 | €257 | €240 |