GAN Lab is an open-source project on GitHub with about 1,541 stars, most recently updated in 2026. GAN Lab is an interactive, visual experimentation tool for Generative Adversarial Networks, created by the Polo Club at Georgia Tech. Running entirely in the browser, it lets you train a small GAN live, watch the generator and discriminator evolve, and build intuition for how adversarial training actually works.
Published on GitHub under the Apache-2.0 license, GAN Lab has attracted a community of about 1,541 stars, which places it among the more visible open-source AI projects in its niche. Development was still active as of 2026, based on the repository’s latest updates. Because the full source code is public, teams can audit how it works, adapt it to their own stack, and self-host it rather than depending on a closed hosted product.
New users can explore the examples and documentation in the repository to understand the main workflows before integrating it into their own projects, and the public issue tracker shows what the maintainers are actively working on and what the community is asking for, which makes it easier to judge project health before adopting it.
GAN Lab is Apache-2.0 open source and completely free to use online or self-host.
GAN Lab is best suited for students, teachers and ML beginners who learn best by experimenting with GANs visually instead of only reading equations. Anyone evaluating it should start with the GitHub repository, where the documentation, examples and issue tracker show exactly what the current version can do.