Coming soon: NVIDIA Tesla P40, 24 GB VRAM

Deep Learning GPU VPS

Train neural networks such as CNNs, small transformers and GANs on an NVIDIA Tesla P40 (24 GB VRAM, Pascal architecture). GPU servers are not orderable yet; contact us to be notified when they are.

$ pip install torch torchvision && python -c "import torch; print(torch.cuda.is_available())"
# Example install command

What is Deep Learning on a GPU VPS?

Deep learning needs GPU acceleration to train neural networks in reasonable time. A GPU server gives you one GPU for your own experiments.

Deep Learning on a VPS.org GPU server

Framework Choice

PyTorch, TensorFlow, JAX or any CUDA framework that still supports Pascal GPUs.

Consistent Speed

The GPU is not shared, so training speed does not depend on other customers.

24 GB VRAM

Room for mid-sized architectures and batch sizes.

Long Jobs

A persistent server can run long training jobs; save checkpoints as you go.

Popular Deep Learning Use Cases

CNN training
Transformer models
GAN training
Reinforcement learning
AutoML experiments
Neural architecture search

Planned GPU Specifications

GPUNVIDIA Tesla P40
VRAM24 GB GDDR5
CUDA Cores3,840
FP3212 TFLOPS
INT847 TOPS
Memory BW346 GB/s
ArchitecturePascal (GP102)
PassthroughPCIe passthrough

Frequently Asked Questions

What is Deep Learning on a GPU VPS?

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Deep Learning can use an NVIDIA GPU to speed up its work. VPS.org GPU servers are not available to order yet; contact us to hear when they are. Deep Learning is a general GPU-accelerated workload. Make sure your software has CUDA support and that your driver / runtime versions match the workload requirements for Deep Learning.

How do I set up Deep Learning on a GPU VPS?

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GPU servers are not available to order yet. Today you can run Deep Learning on a regular CPU plan, where it works far more slowly than on a GPU: SSH in and run pip install torch torchvision && python -c "import torch; print(torch.cuda.is_available())".

How much VRAM do I need for Deep Learning?

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VRAM needs for Deep Learning depend on the model and batch size; check the project documentation for current figures.

How much would a GPU server for Deep Learning cost?

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GPU pricing will be published when GPU servers can be ordered. Contact us if you want to hear when that happens.

Can I run other tools alongside Deep Learning?

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Yes. Every VPS.org server comes with full root access, so you can run other tools alongside Deep Learning within the server's RAM and storage.

Do I get full root on the Deep Learning GPU VPS?

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Every VPS.org server comes with full root SSH access, so you can install drivers, libraries and Deep Learning however you need.

Does VPS.org preinstall CUDA for Deep Learning?

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No. No server comes with a CUDA runtime or NVIDIA driver preinstalled, and GPU servers are not available to order yet. You install the versions Deep Learning needs yourself.

Does my Deep Learning GPU VPS persist between sessions?

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Yes. VPS.org servers are persistent virtual machines, not ephemeral instances: Deep Learning models, configs and data stay on the server's SSD storage until you delete them.

Where should I store data for my Deep Learning workload?

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Keep working data on the server's SSD for fast access during Deep Learning runs, and copy finished artifacts (weights, generations, embeddings) to storage outside VPS.org; snapshots and backups stay on the same storage cluster.

Can I scale my Deep Learning GPU VPS later?

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You can upgrade any VPS.org server to a larger plan from the control panel; the resize restarts it and your Deep Learning install carries over. GPU servers are not available yet.

Are backups available for my GPU VPS?

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Yes. Backups are a paid add-on (daily +30% of the plan price, kept 7 days; weekly +20%, kept 28 days) and snapshots are free, which is useful before long Deep Learning runs. Both stay on the same storage cluster as the server.

Can I get a refund?

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Contact support within 30 days of your first purchase to request a refund. GPU servers are not sold yet, so no GPU order is involved.

Want to Run Deep Learning on a GPU Server?

GPU servers are not orderable yet. Tell us about your workload and we will let you know when they are.