alphacube and efficientcube
These are competing implementations of Rubik's Cube solvers by the same author, where efficientcube represents a newer state-of-the-art approach that has superseded alphacube's "powerful & flexible" design, explaining why only the former is actively downloaded despite lower adoption.
About alphacube
kyo-takano/alphacube
A powerful & flexible Rubik's Cube solver
About efficientcube
kyo-takano/efficientcube
State-of-the-Art method for solving the Rubik's Cube
Uses self-supervised learning on backward state trajectories from the goal state rather than forward exploration, enabling DNNs to solve Rubik's Cube, 15 Puzzle, and Lights Out with fewer training iterations. Includes pretrained TorchScript models and integrates beam search decoding with configurable width to balance solution optimality against computational cost. Provides standalone Jupyter notebooks for training and inference on Colab/Kaggle, plus a Python package with straightforward API for applying scrambles and retrieving solution paths.
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