One-click AI

Paid from prepaid credits — added once, from $5.00; what an app does not use stays in your balance.

Pick what you want to do. We choose a GPU that fits, start the app, and open it for you — usually within a minute or two; the first time an app runs on a machine, its download can take a few minutes, and that wait is not charged. You only pay for the time you use, and you can stop any second.

📓
Experiment with AI in a notebookPython notebook (PyTorch)
Python notebook (PyTorch)Write and run code · pytorch

Type a little Python, see the result right below — the classic way to learn and try AI.A JupyterLab notebook with PyTorch and the GPU already wired up. The classic way to experiment.

  • JupyterLab in your browser
  • PyTorch + CUDA ready
  • Files persist for the whole rental
$0.09 /hour
on an Intel Core i7-14700F — CPU only · 21 GB · Asia-Pacific

Run `torch.cuda.is_available()` in the first cell — it says True.

💬
Chat with an AIRun an open LLM (Ollama)
Run an open LLM (Ollama)Chat with an AI · ollama

Your own ChatGPT-style assistant, on a GPU you rent: what you type goes to that machine, not to an AI company. It is someone else’s computer, so keep secrets out of it.Your own ChatGPT-style model, running on hardware you rented — your chats go to that machine, not to an AI company.

  • Chat right here in your browser
  • Pick any open model (Llama, Qwen, Phi…)
  • Or use it from code over a normal API
$0.09 /hour
on an Intel Core i7-14700F — CPU only · 21 GB · Asia-Pacific

Pick a model on the rental page and start typing — no terminal, no setup.

🚀
Give your app an AI brainOpenAI-compatible server (vLLM)
OpenAI-compatible server (vLLM)Put a model behind an API · vllm

Runs a model behind the same kind of web address OpenAI uses, so your app or script can talk to it.Serve a model with an OpenAI-compatible API, so existing code can point at it by changing one URL.

  • Qwen2.5-7B served for you
  • OpenAI-compatible endpoints
  • Swap in any open model
unavailable right now

No GPU with at least 24 GB is free right now — try again shortly.

📊
Notebook for TensorFlow projectsTensorFlow notebook
TensorFlow notebookWrite and run code · tensorflow

The same notebook, set up for TensorFlow and Keras — pick it if your course or code uses them.A JupyterLab notebook with TensorFlow 2 and GPU support, for Keras and TF workflows.

  • JupyterLab in your browser
  • TensorFlow 2 + GPU
  • Files persist for the whole rental
$0.09 /hour
on an Intel Core i7-14700F — CPU only · 21 GB · Asia-Pacific

Run `tf.config.list_physical_devices("GPU")` to see the card.

⚡
Just give me a GPUJust give me a GPU
Bring your own setupBring your own setup · cuda

A clean machine and a terminal, for when you know exactly what you want to install.A clean CUDA machine and a terminal. Install whatever you like — fastest to start.

  • CUDA 12.4 on Ubuntu 22.04
  • A real shell in your browser
  • Full control
$0.12 /hour
on an NVIDIA RTX 5070 · 12 GB · Asia-Pacific

Open the Terminal and run `nvidia-smi`.

How this works

1 You pick an app — not a GPU. We match the smallest card that runs it well and show the price first.

2 We rent it from your credits, start the app, and take you to it — it opens as soon as it answers.

3 Stop whenever you like — unused time goes back to your credits automatically.