GPU Compute

GPU Blades

SSH into real GPUs in minutes. Multi-user isolation, auto-provisioning, and pre-configured environments for AI competitions, workshops, and courses.

Getting Started

Three Steps to GPU Access

1

Install

pipx install rb-cli

Works on macOS, Linux, and Windows/WSL.

2

Join

rb event join CUDA-2026

Enter the event code shared by your instructor.

3

Connect

rb blade ssh

SSH into your GPU. PyTorch, CUDA, and tools pre-installed.

Hardware

Available GPUs

From lightweight demos to multi-GPU distributed training.

GPU Type VRAM Best For Price
RTX 4000 Ada 20 GB Light workloads & demos €0.99/hr
L40S 48 GB Training & workshops €1.99/hr
RTX 6000 Ada 48 GB Training & workshops €1.99/hr
MI300X 192 GB Large model inference €2.49/hr
H100 80 GB Large model training €4.29/hr
H200 141 GB Large model training €4.49/hr
L40S x4 192 GB Large model training €7.99/hr
L40S x8 384 GB Distributed training €15.99/hr
MI300X x8 1536 GB Multi-GPU inference €19.99/hr
H100 x8 640 GB Multi-GPU workloads €29.99/hr
H200 x8 1128 GB Multi-GPU workloads €34.99/hr
Status

GPU Availability

Live availability status across our GPU fleet.

RTX 4000 Ada L40S RTX 6000 Ada MI300X H100 H200 L40S x4 L40S x8 MI300X x8 H100 x8 H200 x8

Check availability on the pricing page

Features

Built for GPU Workloads

Multi-User Isolation

Up to 20 users share a single GPU with full container isolation. Each user gets their own environment.

Auto-Provision at Event Start

GPU blades spin up automatically when your event starts. No manual provisioning needed.

Auto-Teardown at End

When the event finishes, blades are destroyed automatically. No forgotten instances running up bills.

Pre-Configured Environments

PyTorch, TensorFlow, JAX, and CUDA pre-installed. Start training immediately.

VS Code Remote-SSH

Connect with VS Code Remote-SSH for a full IDE experience on GPU hardware.

Blade Failure Auto-Recovery

If a blade fails, a replacement is provisioned automatically. Your users stay connected.

CLI

Everything From the Terminal

The rb CLI gives you full control over your GPU blades.

Connect
$ rb blade ssh
Connected to gpu-blade-abc123
(L40S, 48GB VRAM)
student@gpu:~$
Configure
$ rb blade config
GPU: L40S
VRAM: 48 GB
Users: 20/20
Status: active
Transfer
$ rb blade scp model.pt :
Uploading model.pt...
100% | 2.4 GB | 45 MB/s
✓ Transfer complete

Ready to SSH into a GPU?

Install the CLI and connect to a GPU blade in minutes.