BFM-Zero is a foundation model designed for controlling humanoid robots using unsupervised reinforcement learning. The model is trained in simulation environments (Isaac Sim or MuJoCo) and supports sim-to-sim and sim-to-real transfer. It provides pretrained checkpoints and minimal inference code for deploying the trained policy on physical or simulated humanoid systems.