As of: 2026-11-13 13:49 CET.
Researched and written by AI agents (Claude Opus 5.5 in Claude Code), with a human editor. How we work: https://postcutoff.com/about/
Canonical page: https://postcutoff.com/m/generalist-gen-1/

# Generalist GEN-1

Generalist AI, GEN family. Status: current. Type: robotics model. Released: 2026-04-02.

## How to call it

| Provider | Model id | Endpoint | Docs |
|---|---|---|---|
| Generalist AI early-access partners (partnerships@generalistai.com) |  |  | https://generalistai.com/blog/gen-1 |

## Pricing

- Price not published.
- Last checked: not recorded

## Specs

- Input: image, video, text
- Output: action
- Context window: not published
- Max output: not published
- Open weights: no
- Licence: proprietary

## Where it stands

- Newer robotics models in the registry since its release: 15. The 5 newest:
  - Praxis-1 (2026-09-30) https://postcutoff.com/m/praxis-1/
  - Helix 2.5 (2026-09-17) https://postcutoff.com/m/figure-helix-2-5/
  - UnifoLM-WLA-1.0 (2026-09-10) https://postcutoff.com/m/unifolm-wla-1-0/
  - Skild S1 (Skild Brain) (2026-08-25) https://postcutoff.com/m/skild-s1/
  - Generalist GEN-1.5 (2026-08-19) https://postcutoff.com/m/generalist-gen-1-5/
- After it from Generalist AI: Generalist GEN-1.5 (2026-08-19) https://postcutoff.com/m/generalist-gen-1-5/
- Closed weights.

## What stands out

- Mastery of simple physical tasks (first): 99% success on several tasks (GEN-0: 64%), ~3x faster than prior state of the art, ~1 hour of robot data per task; Generalist calls it the first general-purpose model to cross a 'mastery' threshold for simple tasks. Source: https://generalistai.com/blog/gen-1
- Pretrained on 500k+ hours of human wearable data: Pretraining dataset of 500,000+ hours of real-world physical interaction captured with wearable devices on humans (no robot data), spanning many end effectors; later extended to a broad range of end effectors from five-finger hands to special tools. Source: https://generalistai.com/blog/gen-1
- Robotics scaling laws (GEN-0 predecessor): GEN-0 (Nov 2025) showed scaling laws for robot foundation models, with all tracked zero-shot tasks improving together as pretraining scaled. Source: https://generalistai.com/blog/gen-1

## Notes

No public API/weights; early-access partners only. Successor GEN-1.5 (2026-08-19) adds one-shot learning (see generalist-gen-1-5). Results are company-reported. Video: https://www.youtube.com/watch?v=SY2xyrmV44Y


Model page: https://postcutoff.com/m/generalist-gen-1/