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CLI enabling Free Cloud GPU access in your terminal for learning CUDA

nvcc demo

# Install cgpu
npm i -g cgpu
# First run will launch an interactive setup wizard
# Connect to a cloud GPU instance quickly without setup any time after that
cgpu connect
# Run a command on a cloud GPU instance without a persistent terminal (but mantaining file system state)
cgpu run nvidia-smi

Serve Gemini for Free as OpenAI-compatible API

You can start a local server that proxies requests to Google Gemini using the cgpu serve command. This allows you to use Gemini with tools that expect an OpenAI-compatible API.

# Start the server on port 8080
cgpu serve

# Specify port and model
cgpu serve --port 3000 --default-model gemini-2.0-flash

For an example of using this with the OpenAI client, check out python_example. This requires you have the gemini cli installed.

Vision

The primary goal of this project to facilitate a high quality developer experience for those without GPUs who would like to learn CUDA C++ This means 3 main things:

  1. Free: Avoid having to pay while learning.
  2. Highly Available: Run quickly instead of having to wait in a queue so that users can compile quickly and learn faster.
  3. In User Terminal: Allows developers to use their own devtools/IDEs (Neovim, Cursor, etc) so they can be most productive.

Next Steps

I will continue to add to the CLI as I find more free compute sources and developer experience improvements. To see what I am currently planning to add check out the Issues tab on Github. Feel free to create new Issues for suggestions/problems you run into while learning!

Login Demo

login.mov