cgpu
v0.1.4
Published
Free cloud GPUs for learning CUDA
Readme
CLI enabling Free Cloud GPU access in your terminal for learning CUDA

# 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-flashFor an example of using this with the OpenAI client, check out python_example. This requires you have the gemini cli installed.
Vision
https://github.com/user-attachments/assets/93158031-24fd-4a63-a4cb-1164bea383c3
### 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!