TD-MPC2 is a model-based reinforcement learning algorithm that learns world models to enable continuous control across multiple domains. The implementation supports both single-task online RL and multi-task offline RL training, with a single set of hyperparameters achieving strong performance across diverse robotics tasks. The repository includes over 300 model checkpoints and supports episodic RL tasks.