
From terminal to isolated compute
Self-service AMD GPU compute with no sales handoff in the way.
First launch steps
01
Create an account
Log in to the terminal UI and create a team.
02
Add credits
Add credits with Stripe or crypto stablecoins (USDT and USDC).
03
Launch an instance
Choose a GPU configuration and start your isolated compute.
Connect via SSH
Log in to the Hot Aisle terminal UI with your favorite console application and create your team, add credits, and provision compute.
ssh admin.hotaisle.appFor a terminal app, use Ghostty on macOS and Linux, or WezTerm on Windows.
Next steps
Your VM already comes with a recent ROCm setup, and Docker or Podman is ready to go. AMD recommends using their dev containers, which is a lot easier than installing everything by hand, and their docs are solid. If you have any feedback, we’d be happy to pass it along to them.
- Quickstart with AMDStart your container with an external volume so your work remains available after the container exits.View Docker guide
- Automate with dstackAutomate deployments and make better use of your VM capacity with our dstack API integration.View dstack integration
- ChatXYZ + Open WebUIBuild a private ChatGPT-style interface with Open WebUI, vLLM, and an SSH tunnel to your GPU VM.Read blog post
- OpenCode + vLLMConnect OpenCode to a self-hosted vLLM server on Hot Aisle with SSH tunneling and AMD MI300X GPUs.Read blog post
- PyTorch official guideUse AMD’s official installation guide to get PyTorch running with ROCm.View PyTorch guide
- TinyGrad setupFollow the TinyGrad project setup instructions for an alternative lightweight stack.View TinyGrad repository
Build from your own tooling
The same platform is available through the API, CLI, and cloud-init templates.
Talk to a real person
hello@hotaisle.aiA real human will reply, not an AI bot or support agent.
