# Runway Opens the Weights of Its Video-Trained Robot Model, the Top World Action Model on Nvidia's Leaderboard but Fifth Overall

Times of AI Desk · 2026-11-12 · Models

[https://timesof.ai/2026/11/runway-praxis-1-open-weights-robot-model-robolab](https://timesof.ai/2026/11/runway-praxis-1-open-weights-robot-model-robolab)

> Runway released Praxis-1 on November 11 with open weights under Apache 2.0, including inference and fine-tuning code. The 27-billion-parameter model predicts video and robot actions together and scores 46.2% success on Nvidia's RoboLab-120 simulation benchmark, first among world action models and ahead of FLUX 3 Action (42.9%). On the leaderboard's overall table it ranks fifth, behind systems including an agentic language-model policy at 86.0%. Runway says it adapts to new robots with light fine-tuning.

Runway, best known for video generation, is giving away the robot model it built on that video. **Praxis-1** is now available with open weights for commercial use, and on Nvidia's robotics leaderboard it is the strongest model of its type. The leaderboard also shows the limit of that claim: four systems of other kinds score higher.

## What Runway released

Runway made Praxis-1 available on **November 11**, after introducing it in September. Per Runway:

- It is a **27-billion-parameter** mixture-of-experts diffusion transformer that predicts future video and robot actions together, a "world action model."
- Weights, inference code and fine-tuning code, including LoRA, are released under **Apache 2.0**, on GitHub and Hugging Face with LeRobot support, and it runs on Nvidia hardware from data center GPUs to the Jetson Thor robot computer.
- Fine-tuned on Google's RT-1 robot, which it had not seen in training, it reached **80.0%** success on the SimplerEnv test against **52.4%** for the original RT-1 policy. Launch partners have run it on a humanoid, an industrial arm and a warehouse robot.

## Where it ranks

On Nvidia's **RoboLab-120** simulation leaderboard, Praxis-1 succeeds in **555 of 1,200** episodes, or **46.2%**, ranking first among world action models, ahead of Black Forest Labs' FLUX 3 Action at 42.9% and Nvidia's Cosmos3 Nano policy at 36.8%. In the overall table, which includes agentic language-model systems, it ranks **fifth**: the leader is listed at **86.0%** and a vision-language-action model at 49.2%. The leaderboard flags several entries as using simulation data in training; Praxis-1 is not flagged. Nvidia's own GR00T N1.6 is listed at 7.2%; its newer GR00T 2, which [Nvidia says ranks near the top of the field's leaderboards](https://timesof.ai/2026/11/nvidia-gr00t-2-world-action-model-71-percent-one-demo-corl), does not appear on this table.

## Limits

- RoboLab-120 is a simulation benchmark. Nvidia says its rankings correlate strongly with a real-world benchmark, but simulation success is not deployment success.
- Runway's statement that Praxis-1 "outperforms every open-weight VLA" depends on which entries count as open-weight; the leaderboard's top entries are of different types and settings and are not directly comparable.
- The RT-1 and partner results are Runway's own.
- The leaderboard says submissions are temporarily paused; rankings were checked on November 12.

## Sources

- [Runway: Praxis-1 Is Now Available (November 11, 2026)](https://runway.com/news/company-news/praxis-1-is-now-available)
- [Nvidia Research: RoboLab Leaderboard (accessed November 12, 2026)](https://research.nvidia.com/labs/srl/projects/robolab/leaderboard.html)