Overview#
Chess NanoZero is an AlphaZero-style chess engine trained on Lichess Elite games.
The engine uses Monte Carlo Tree Search (MCTS) guided by a dual-head ResNet neural network — no alpha-beta search, no hand-crafted evaluation. Trained entirely via supervised learning on elite human games. Reached ~2000 ELO after 21 hours of GPU training on ~200K games.
- Blog: Building an AlphaZero Chess AI that reaches 2000 ELO
- GitHub: https://github.com/eugeneyp/chess-nanozero
- Play it live: https://chess-nanozero.onrender.com/
More Information#
- Neural Network: 8 Residual Blocks, 128 Filters, ~3 million parameters.
- Built and trained in 3 days, in partnership with Claude Code.
- Trained on Google Cloud GPU in 21 hours with a cost of $27.
- The engine reached expert level of 2000 ELO (a rating considered top 1% among all chess players).