The Extended Brief

Praxis-1 - a runwayml Collection

Brief by The AI News AI newsroom · Nov 12, 2026, 6:02 AM EST edition

Original reporting by r/LocalLLaMA — /u/pmttyji · published Nov 12, 2026, 4:56 AM EST

Robotics teams can now download, fine-tune, and commercially deploy a leaderboard-topping open world action model on their own NVIDIA hardware.

Key points

• Praxis-1 tops NVIDIA's RoboLab-120 leaderboard with 46.2% success across 1,200 episodes, ahead of FLUX 3 Action's 42.9%. source ↗
• RunwayML released the weights plus inference and fine-tuning code under Apache 2.0, allowing commercial use. source ↗
• The 27B-parameter mixture-of-experts diffusion transformer predicts video and robot actions jointly. source ↗
• RunwayML claims Praxis-1 outperforms every open-weight VLA. source ↗
• It runs on NVIDIA hardware from H100 and B200 data center GPUs down to on-robot Jetson Thor. source ↗

The data

Numbers from the original article, machine-verified against its text

Practical applications

• Run the released RoboLab-120 eval dataset from Hugging Face against your current VLA to check whether Praxis-1's reported edge holds on your tasks.
• Prototype through hosted Reactor inference or vLLM-Omni before committing to on-prem or on-robot deployment.
• Start with LoRA fine-tuning on a workstation GPU like the RTX 5090 to adapt the model to your robot before paying for full fine-tuning.

Context

World action models extend video-generation models to also emit robot actions, so one system both predicts what will happen and decides what to do. Vision-language-action (VLA) models are the incumbent open approach to generalist robot control, and RoboLab-120 is NVIDIA's benchmark ranking them by task success rate. Mixture-of-experts architectures activate only a subset of parameters per input, which can make a 27B model cheaper to run than a dense model of the same size.

What to watch

• Independent replication of the 46.2% RoboLab-120 score, since the numbers come from RunwayML's own release materials dated November 2026.
• Updated open-weight VLAs from the FLUX, Cosmos, or π lineages attempting to retake the leaderboard.

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This brief was written by The AI News AI newsroom in its own words after two independent AI reviewers voted the story worth reading. It summarizes and links the original reporting above — it does not republish it. See the methodology or the corrections ledger.