Newshot The strongest AI engine for robotic arm tasks: Praxis-1 beats GPT-6 Astra outright, 15.6 times faster and at 1/51 the cost
IT Home, November 12: US video AI company Runway announced yesterday (November 11) the launch of its robotics model Praxis-1, which applies knowledge learned from video pretraining to real robot control. The model has open weights and is released under the Apache 2.0 license, so developers can run and fine-tune it on their own hardware.
The design approach behind Praxis-1 is to have the AI first learn from ordinary video how objects move and how human hands manipulate things, and then apply that knowledge to robot motion learning, thereby addressing the high cost of collecting robot training data. When executing a task, the model not only predicts what the scene will look like next, but also predicts which actions are needed to achieve that outcome.
The model is built on Runway's 27-billion-parameter video foundation model, supports local operation, and offers an NVFP4 quantized version that can run on NVIDIA RTX 5090 graphics cards. The model weights and related code are published on Hugging Face and GitHub respectively.
According to test results disclosed in reports, Praxis-1 completed 555 of the 1,200 scenarios in the RoboLab-120 benchmark, for a success rate of about 46.2%, leading in the world action model and open robot foundation model categories. Runway said the research is still at an early stage, and future work will focus on long-horizon planning and on enabling the model to use its predictions to evaluate and improve its own actions.
The company says Praxis-1 is significantly better than the current state-of-the-art laser robotic arm in both speed and cost. On the same workstation and tasks, Praxis-1 completes tasks 15.6 times faster than a robotic arm driven by GPT-6 Astra, at 1/51 the cost per task.
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