# Runway's Praxis-1 hits 80.0% on SimplerEnv after RT-1 fine-tuning

> Original title: We think the most scalable source of robotics data is general video. A model trained to predict that video learns how objects behave, how...

- Source: Runway
- Published: 2026-11-11T15:04:28.000Z
- Bad Influence: https://badinfluence.news/items/l7jjaeowyx4a9rjms4mmat1u4
- Original: https://x.com/runwayml/status/2120533123649941845

## Summary

Runway says its Praxis-1 model, fine-tuned on Google's RT-1 robot, a robot it never saw in training, reaches 80.0% on SimplerEnv. The original RT-1 policy scores 52.4% on the same benchmark. Runway argues general video is the most scalable source of robotics data, since a model trained to predict video learns how objects behave and how tasks unfold.

## Post

We think the most scalable source of robotics data is general video. A model trained to predict that video learns how objects behave, how hands move and what a task looks like partway through, giving it a head start on new embodiments.

Fine-tuned on Google’s RT-1, a robot it never saw in training, Praxis-1 reaches 80.0% on SimplerEnv, against 52.4% for the original RT-1 policy.

![](https://badinfluence.news/api/img-proxy?u=https%3A%2F%2Fpbs.twimg.com%2Fmedia%2FHW2lo5vbcAA7qJW.jpg&mode=thumb&exp=1794700800&sig=122beebc5a1742c3)