We open-source a total of 324 TD-MPC2 model checkpoints, including 12 multi-task models (ranging from 1M to 317M parameters) trained on 80, 70, and 30 tasks, respectively. We are excited to see what the community will do with these models, and hope that our release will encourage other research labs to open-source their checkpoints as well.

We recommend starting out with the 48M checkpoints, which strike a good balance between model size and performance. The 317M checkpoints are the largest models we trained, and achieve the best performance on both task sets. However, they are also the most expensive to train and evaluate. Note that "Score" is not comparable across task sets.

We organize single-task checkpoints by task domain, totalling 312 checkpoints for 104 tasks across 4 domains. Most, but not all, models were trained to convergence and produce expert behavior.

We also provide raw per-task and per-seed scores for all 104 tasks. They can be downloaded here.