GEN-1

Architecture

Physical foundation model trained from scratch on real-world data at scale

Key facts

Mastery 99% claims (primary Generalist)

Generalist AI's April 2 2026 GEN-1 blog says GEN-1 improves average success rates to 99% on tasks where previous models achieve 64%, completes tasks roughly 3x faster than prior SOTA, and requires about 1 hour of robot data for those results. It defines mastery as reliability, speed, and improvisation. Treat benchmark comparisons as company-stated (Generalist AI)

Pretrain data scale (primary Generalist)

The same Generalist blog says GEN-1 is trained from scratch on a dataset that now includes over half a million hours of high-fidelity physical interaction data, with the base foundation trained without robot data (using wearable human interaction data) and task adaptation using roughly one hour of robot data. Treat dataset size as company-stated (Generalist AI)

Mastery threshold claims (primary Generalist)

Generalist AI (Apr 2 2026) introduced GEN-1 as an embodied foundation model it says crosses a mastery threshold on simple physical tasks, improving average success rates to 99% on tasks where prior models achieved 64%, completing tasks roughly 3x faster than prior SOTA, with about 1 hour of robot data per result. Treat performance claims as company-stated (Generalist AI)

GEN-1.5 one-shot learning

Generalist AI's follow-on GEN-1.5 post describes its embodied foundation-model research as targeting one-shot learning for physical tasks; this is the company's stated continuation of the GEN-1 line (Generalist GEN-1.5).

Beyond-world-models position

Generalist AI says its physical-intelligence approach goes beyond using a world model alone by connecting perception, reasoning, and action in an embodied system; this is a company position, not an independent evaluation (Generalist beyond world models).

Developed by (1)

• Generalist AI

Common questions

Sources (3)

1. https://generalistai.com/blog/gen-1 ↗
2. https://generalistai.com/blog/gen-1.5 ↗
3. https://generalistai.com/blog/beyond-world-models ↗

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