Generalist raises $400M to scale physical AI

Generalist, an embodied foundation model development company, announced a $400 million funding round, bringing its total raised to more than half a billion dollars.

The company said that the capital will be used to accelerate its mission of building physical AGI, and making it useful to everyone.

Generalist said that its new major investors include Radical Ventures (lead), 8VC, Union Square Ventures, Hanabi Capital and Norwest. The major existing investors also participated in this round, including NVIDIA, Boldstart Ventures, Spark Capital, Bezos Expeditions and NFDG. New angel investors include Bin Lin, Fei-Fei Li and Naval Ravikant.

The frontier lab for robot intelligence

In November 2025, the company launched GEN-0, which it said is its embodied foundation model that brought robotics into the pretraining era. Generalist said that for the first time, models trained on an unprecedented scale of real-world data demonstrated scaling laws in robotics: proof that more physical experience and larger models can predictably produce more capable systems.

At NVIDIA GTC 2026, Generalist showcased GEN-0 alongside Universal Robots, demonstrating the robotics foundation model’s dexterity and reliability.

And in April 2026, the company launched GEN-1, which Generalist said showed where that path leads: models that cross into commercial viability. Across a wide range of dexterous capabilities, the company said that GEN-1 demonstrated traction toward the practical thresholds required for real deployments, including:

• 99% reliability on diverse tasks
• Execution up to 3x faster than prior states
• The ability to learn complex new physical skills
• The capacity for creative problem solving through emergent improvisational intelligence.

The company said that these results are not the product of a single idea; they are the compounding result of thousands of decisions, across data, models, hardware, infrastructure, operations and deployment, made by its team.

Generalist said that the funding gives the company the necessary resources to continue to lead in scaling robot learning:

• From building its next-generation models
• To scale its physical data engine
• From expanding its compute and training infrastructure
• And working with the industries that will bring these systems into everyday use

Generalist said that its goal is not to tie itself to any single method or label, but to build whatever is needed to make physical AGI real.