MolmoAct2 MolmoAct2 is an open vision language action model for robot control. It builds on Molmo2 ER, an embodied reasoning VLM backbone, and connects the autoregressive VLM to a flow matching continuous action expert through per layer KV (key value) conditioning. This checkpoint is the post trained, multi embodiment MolmoAct2 model. It is intended as a foundation checkpoint for further robot fine tuning rather than as a ready to run policy for a single deployment setting. Quick Links 📂 Models: Models, Finetuned Models 📂 Datasets: MolmoAct2 BimanualYAM Dataset, MolmoAct2 Datasets, Molmo2 ER Datasets 📄 Paper: arXiv:2605.02881 💻 Code: allenai/molmoact2 🎥 Blog Post: MolmoAct2 Intended Use Use this checkpoint for further fine tuning on a target robot embodiment or benchmark. It contains the VLM and continuous action expert weights, plus normalization metadata for the post training mixture in norm stats.json . This model card intentionally does not include direct policy inference code. For ready to run inference examples, use one of the fine tuned checkpoints such as MolmoAct2 LIBERO , MolmoAct2 DROID , MolmoAct2 BimanualYAM , or MolmoAct2 SO100 101 . Model and Hardware Safety Mol…
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