Sim-trained ZAP robot policy hits 96.7% on real tasks
A 27B vision-language model fine-tuned only in simulation matches GPT-6 Astra and beats MolmoAct2's 33.3% in the same harness.
A 27B vision-language model fine-tuned only in simulation matches GPT-6 Astra and beats MolmoAct2's 33.3% in the same harness.
Across 16 frozen model-benchmark pairs it lowered chunk inference cost, with up to 1.48 times speedup and higher success in 14.
FastOPD distills large vision-language-action models into few-step students that keep most performance at much lower latency.
RoboHarm benchmark found GPT-6 Astra, Claude Fable 5.1, and MolmoAct2 rarely refuse dangerous robot-arm commands, completing most harmful physical tasks.
Early StationeryBench robotics results show OpenAI's GPT-6 Astra far ahead of Ai2's MolmoAct2 at dual-arm manipulation, completing 7 of 100 tasks versus zero.
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