GPU Servers · AI
GPU Servers for AI Training
Dedicated NVIDIA GPU servers built for training and fine-tuning machine-learning models — CUDA-ready, full root, and never throttled by shared tenants.
Training and fine-tuning need consistent GPU throughput and fast access to large datasets. Our dedicated GPU servers give you the entire card plus NVMe-backed storage, so data loading keeps the GPU fed instead of starving it.
You get full root and IPMI, so you control the CUDA/cuDNN versions and your framework stack end-to-end. Run PyTorch, TensorFlow, JAX, or a custom pipeline, with 24/7 support if you hit a driver or environment snag.
CUDA-ready
Install any CUDA/cuDNN version for your framework of choice.
Dedicated GPUs
No GPU sharing — full, consistent throughput for training runs.
NVMe datasets
Fast local NVMe keeps large datasets close to the GPU.
Big RAM
Plenty of system memory for data pipelines and caching.
Root + IPMI
Full control of the OS and out-of-band access.
24/7 support
Help with drivers and environments, any hour.
Ready to get started?
Enterprise infrastructure with NVMe storage, DDoS protection, and 24/7 managed support — included on every plan.
View GPU ServersFrequently asked questions
Which frameworks are supported?
Any — you have full root, so PyTorch, TensorFlow, JAX, and custom stacks all work. Install the CUDA version they need.
How do I get my dataset onto the server?
Transfer over SSH/rsync/S3 to the local NVMe storage, or mount external storage. We can advise on the fastest path for large datasets.
Can I scale to multiple GPUs?
Yes — reach out for multi-GPU builds and current availability.
Is the GPU shared with other users?
No. It’s a dedicated bare-metal server; the GPU is exclusively yours.