# GEN-0 (and GEN-1), brain

Generalist AI (founded 2024 in San Mateo, California by chief executive Pete Florence, a former DeepMind senior research scientist, with Andy Zeng, also ex-Google DeepMind, and Andrew Barry, ex-Boston Dynamics, and backed by Nvidia) builds embodied foundation models trained directly on raw physical-interaction data. Its GEN-0 model, published in a November 4, 2025 research blog, was tested at one to ten-plus billion parameters on more than 270,000 hours of real manipulation trajectories growing by roughly 10,000 hours a week, and reports a scaling phase transition around 7 billion parameters; a successor, GEN-1, followed in April 2026. The models are proprietary with no open weights. The registry records the brain at research maturity because its capability is demonstrated rather than deployed: it runs across 6-, 7-, and 16-plus-degree-of-freedom semi-humanoid robots in lab and benchmark settings, but there is no named hardware partner, customer, or production deployment, and the robot wiring is in-house and captive. The artifact is real and substantive enough to clear the registrable bar even without peer review, but its benchmark numbers, including a 99-percent task-success claim, the 270,000-hour figure, and the scaling claims, are self-reported and not independently reproduced, there is no arXiv paper or formal model card, the funding amount and valuation are undisclosed, and there is no named robot-platform partnership.

- **Slug:** gen-0
- **Type:** Foundation model
- **Maturity (DEPLOY ladder):** Research
- **Open source:** no

## Architecture

Embodied/manipulation foundation model (generalist VLA-class) trained on raw physical-interaction data; ~7B-param scaling phase transition reported.


## Key facts

- **Model:** GEN-0 (Nov 4 2025): embodied foundation model trained directly on raw physical-interaction data; tested at 1B/6B/7B/10B+ params; >270,000 hrs of real manipulation trajectories growing ~10,000 hrs/week; reports a 'scaling phase transition' at ~7B params. GEN-1 (Apr 2026) successor. Proprietary, no open weights.
- **Deployed wiring: demonstrated, NOT deployed:** Runs across 6-DoF, 7-DoF, and 16+-DoF semi-humanoid robots in lab/benchmark settings. NO named hardware partner, customer, or production deployment. Robot wiring is in-house/captive.
- **Provider:** Generalist AI (founded 2024, San Mateo CA; founders Pete Florence (CEO, ex-DeepMind), Andy Zeng (ex-Google DeepMind), Andrew Barry (ex-Boston Dynamics); Nvidia-backed).
- **Cap-flag:** Benchmark numbers (99% task success, 270k hrs, scaling claims) are SELF-REPORTED, not independently reproduced; no arXiv/peer-reviewed paper or formal model card (self-published research blog). Funding amount/valuation undisclosed; no named robot-platform partnership; GEN-1 SOTA-comparison claims unverified.


## Developed by (1)

- [Generalist AI](/companies/generalist-ai.md)


## Sources (3)

1. **Generalist GEN-0 embodied foundation model (270k+ hrs data; 7B scaling phase transition)** · https://generalistai.com/blog/nov-04-2025-GEN-0
2. **Generalist AI (founders ex-DeepMind/BD; Nvidia-backed stealth startup)** · https://techcrunch.com/2025/03/19/a-key-deepmind-robotics-researcher-left-google-and-nvidia-has-already-backed-his-stealth-startup/
3. **Generalist releases GEN-1 robotic-intelligence foundation model (Apr 2026)** · https://siliconangle.com/2026/04/06/generalist-releases-gen-1-highly-capable-robotic-intelligence-ai-foundation-model/


## Common questions

### What is GEN-0 (and GEN-1)?

Generalist AI (founded 2024 in San Mateo, California by chief executive Pete Florence, a former DeepMind senior research scientist, with Andy Zeng, also ex-Google DeepMind, and Andrew Barry, ex-Boston Dynamics, and backed by Nvidia) builds embodied foundation models trained directly on raw physical-interaction data. Its GEN-0 model, published in a November 4, 2025 research blog, was tested at one to ten-plus billion parameters on more than 270,000 hours of real manipulation trajectories growing by roughly 10,000 hours a week, and reports a scaling phase transition around 7 billion parameters; a successor, GEN-1, followed in April 2026. The models are proprietary with no open weights. The registry records the brain at research maturity because its capability is demonstrated rather than deployed: it runs across 6-, 7-, and 16-plus-degree-of-freedom semi-humanoid robots in lab and benchmark settings, but there is no named hardware partner, customer, or production deployment, and the robot wiring is in-house and captive. The artifact is real and substantive enough to clear the registrable bar even without peer review, but its benchmark numbers, including a 99-percent task-success claim, the 270,000-hour figure, and the scaling claims, are self-reported and not independently reproduced, there is no arXiv paper or formal model card, the funding amount and valuation are undisclosed, and there is no named robot-platform partnership.

### What type of AI is GEN-0 (and GEN-1)?

GEN-0 (and GEN-1) is a foundation model on the DEPLOY registry. It is proprietary.

### Who developed GEN-0 (and GEN-1)?

GEN-0 (and GEN-1) is credited to Generalist AI on the DEPLOY registry. Each developer attribution is verified via primary sources.

### Which robots run on GEN-0 (and GEN-1)?

No robot models on the DEPLOY registry are recorded as running GEN-0 (and GEN-1). DEPLOY wires brain-to-model connections only when the wiring is verifiable from primary sources; absence may reflect pre-deployment or unverified manufacturer claims.

### Is GEN-0 (and GEN-1) open source?

No. GEN-0 (and GEN-1) is recorded as proprietary on the DEPLOY registry. Model weights and source are not publicly available.

### What is GEN-0 (and GEN-1)'s maturity stage?

GEN-0 (and GEN-1) is at the research stage on the DEPLOY maturity ladder. Research stage means active development without commercial deployments on file.


_API: GET /v1/brains/41097187-969e-4df7-adb6-330d1c60e981 · canonical URL: /brains/gen-0_