Runway’s Praxis-1 world action model for robotics is now available

NVIDIA Corp. — praxis-1 builds on Runway’s work as a founding member of the Cosmos Coalition, advancing open world models for physical AI. | yesterday released Praxis-1, its world action model for robotics.

The model is now available to developers with open weights under the Apache 2.0 license. Runway first announced Praxis-1 in September with launch partners including Noble Machines, Standard Bots, and Ultra. Since then, these companies have been running the model on their own hardware, including a legged humanoid, a six-axis industrial arm, and a dual-arm warehouse robot. “A strong base model goes a long way. Earlier, with Noble Machines, our previous model needed a lot of training to learn their warehouse task: picking up wooden planks one at a time and placing them in a container,” Andy Chen, the head of robotics at Runway, told The Robot Report. “Praxis-1, built with more compute and data, learned it from half an hour of examples and got it right 15 times out of 15. Then we gave it a messy pile of planks it had never seen to clear into bins, and it cleared the whole pile six times out of 10.” “Iterating on feedback from partners makes our models better,” he continued. “Today, Praxis-1 is the top-ranked world action model on NVIDIA’s RoboLab leaderboard, and the top-ranked open-source, end-to-end policy.” Praxis-1 is available on GitHub, on Hugging Face with native LeRobot support, and in vLLM-Omni, with hosted inference on Reactor. Runway said it released everything developers need to run and adapt the model on their own hardware under Apache 2.0, including for commercial use. That covers the weights and the inference and fine-tuning code, with support for both full fine-tuning and low-rank adaptation (LoRA). Praxis-1 runs out of the box across NVIDIA hardware, from data center GPUs such as the H100 and B200, to workstation GPUs like the RTX 5090 and RTX PRO 6000, to Jetson Thor on the robot itself. Praxis-1 builds on Runway’s video foundation models Praxis-1 is a 27B-parameter mixture-of-experts diffusion transformer that predicts video and actions together. On RoboLab-120, Praxis-1 reached 46.2% success across 1,200 episodes, compared with 42.9% for FLUX 3 Action, 36.8% for Cosmos3 Nano and 28.0% for π0.5. It ranks fifth overall on the leaderboard. “The core piece is that a model trained to predict video really understands a lot about the physical world: how objects behave, how hands move, what a task looks like partway through, and so on,” Chen said.