Run TensorFlow and Keras training and inference 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 tensorflow[and-cuda]
# Example install command
TensorFlow is Google's open-source machine learning framework. On a GPU server, TensorFlow runs its operations on the GPU through CUDA.
TensorFlow uses the GPU through CUDA once you install a matching driver and CUDA version.
Build models with the Keras API on top of the GPU backend.
Monitor training with TensorBoard on your own server.
Serve trained models with TensorFlow Serving.
TensorFlow 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. TensorFlow is a training / fine-tuning workload. Plan for long-running jobs: snapshot your VPS regularly and keep a copy of trained weights outside VPS.org.
GPU servers are not available to order yet. Today you can run TensorFlow on a regular CPU plan, where it works far more slowly than on a GPU: SSH in and run pip install tensorflow[and-cuda].
Training VRAM is dominated by the optimizer state plus activations. Full fine-tuning of a 7B LLM needs roughly 24 to 48 GB; LoRA / QLoRA fits in 8 to 16 GB.
GPU pricing will be published when GPU servers can be ordered. Contact us if you want to hear when that happens.
Yes. Every VPS.org server comes with full root access, so you can run other tools alongside TensorFlow within the server's RAM and storage.
Every VPS.org server comes with full root SSH access, so you can install drivers, libraries and TensorFlow however you need.
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 TensorFlow needs yourself.
Yes. VPS.org servers are persistent virtual machines, not ephemeral instances: TensorFlow models, configs and data stay on the server's SSD storage until you delete them.
Keep working data on the server's SSD for fast access during TensorFlow runs, and copy finished artifacts (weights, generations, embeddings) to storage outside VPS.org; snapshots and backups stay on the same storage cluster.
You can upgrade any VPS.org server to a larger plan from the control panel; the resize restarts it and your TensorFlow install carries over. GPU servers are not available yet.
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 TensorFlow runs. Both stay on the same storage cluster as the server.
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.
GPU servers are not orderable yet. Tell us about your workload and we will let you know when they are.