Everything GaasHub does
Six capabilities that make GPU access radically simple.
One Click GPU Access
No configuration, no terminal wizardry, no SSH keys. Click Start in the GaasHub app and your device is connected to a real GPU instantly. Prefix any command with gaashub and it runs on the GPU remotely.
Works With Your Existing Code
You don't rewrite anything. Your existing Python scripts, CUDA code, PyTorch models, TensorFlow pipelines - they all work as-is. GaasHub is invisible infrastructure.
Universal Platform Support
Windows, Mac (Intel and Apple Silicon), Linux (x86, ARM64, ARMv7). One product, every major platform. No platform-specific versions or limitations.
CUDA on Apple Silicon
M1, M2, M3, M4 chips don't support CUDA natively. GaasHub solves this completely - run unmodified CUDA code on your Mac without rewrites, VMs, or compatibility layers.
Edge Device & Robotics Support
Deploy on Raspberry Pi, BeagleBone Black, and other ARM development boards. Give your robot or embedded device access to real GPU compute in real time.
Supports All Major ML Frameworks
PyTorch, TensorFlow, JAX, and standard CUDA. If your code runs on a GPU, it runs on GaasHub.
Up and running in 3 steps
From install to first GPU job in under a minute.
Install
Download and install GaasHub for your platform. Takes under a minute.
Start
Open GaasHub and click the Start button. You're now connected to a GPU.
Run
Open a terminal and prefix your command with gaashub. That's it.
Built for your workflow
From students to robotics engineers - GaasHub works for everyone.
ML Students & Researchers
No GPU? No problem. Run your coursework, experiments, and research on real GPU hardware without buying expensive hardware or navigating complex cloud dashboards.
Mac Users
Finally run CUDA code on your MacBook without any modifications. Stop losing time to compatibility workarounds.
Robotics Builders
Connect your Raspberry Pi or BeagleBone to real GPU compute. Enable real-time computer vision, inference, and CUDA workloads on edge devices that were never designed to handle them alone.
Indie Developers & Startups
Skip the AWS/GCP learning curve entirely. Get GPU access in seconds and get back to building your product.
What you're actually getting
| Supported OS | Windows 10/11, macOS 12+, Ubuntu 20.04+ |
|---|---|
| Supported Architectures | x86_64, ARM64, ARMv7 |
| Supported Frameworks | PyTorch, TensorFlow, JAX, CUDA |
| GPU Hardware | RTX 3060 (12GB VRAM), RTX 3070 (8GB VRAM) |
| Typical Latency | Coming Soon |
| Current App Version | v1.0.38 |
Why Choose GaasHub Over Others
| Feature | GaasHub | RunPod | Vast.ai | AWS SageMaker |
|---|---|---|---|---|
| Setup time | Seconds | 30–60 mins | 30–60 mins | Hours |
| Steps to first run | 1 | 20+ | 20+ | 50+ |
| Windows support | ✓ | ✗ | ✗ | ✗ |
| Mac support | ✓ | ✗ | ✗ | ✗ |
| Linux support | ✓ | ✓ | ✓ | ✓ |
| Raspberry Pi / Edge boards | ✓ | ✗ | ✗ | ✗ |
| CUDA on Mac (Apple Silicon) | ✓ | ✗ | ✗ | ✗ |
| SSH / Docker knowledge needed | ✗ No | ✓ Yes | ✓ Yes | ✓ Yes |
| Run unmodified code | ✓ | ✗ | ✗ | ✗ |
| Technical expertise required | Beginner | Advanced | Advanced | Expert |
| Best for | Everyone - beginners to pros, all platforms | Linux-savvy ML engineers | Budget-focused Linux users | Enterprise teams with DevOps support |
Competitor data based on our own setup experience and public documentation. Last verified March 2026.