Gemini Robotics 2 controls a full humanoid robot with a single learned model

A humanoid robot that walks, crouches and works is now driven by one model, not a stack of controllers.

On July 30, 2026, Google DeepMind unveiled Gemini Robotics 2, its first AI that controls a full humanoid, legs, torso, arms and fingers, under one learned policy.

One brain instead of a stack

Earlier systems, including DeepMind’s own Robotics 1.5, stitched together separate controllers for walking and for manipulation. Gemini Robotics 2 replaces the stack: one vision-language-action model handles the whole body.

In the demo, Apptronik’s Apollo robot walks across a room, picks up a watering can and places it on a shelf while stepping around obstacles. Locomotion, navigation and manipulation, all coming from the same model making the same kind of decisions.

The family and the numbers

The release is actually three models. Gemini Robotics 2 is the action model. ER 2 handles embodied reasoning and multi-step planning. On-Device 2 runs locally on the robot with no cloud dependency, which matters for latency and for anywhere connectivity is not guaranteed.

DeepMind’s reported numbers are striking: success rates up to 92% on fine dexterity tasks like knot tying with 22-degree-of-freedom hands, and adaptation to a new robot body in a few hours with fewer than 200 examples. That last figure is the strategic one. A model that transfers to new hardware that cheaply is not a robot product, it is an operating system candidate.

Availability splits by layer: ER 2 is already in Google AI Studio, while the action models go to early-access partners.

The platform question

The humanoid race just gained a serious operating-system contender, and it sharpens the industry’s central strategic question. One camp bets on a general brain that runs on anyone’s body, which is Google’s play here. The other bets on vertical integration, one company building brain and body together.

If a few hours and 200 examples is really all it takes to move this model onto new hardware, the brain-for-any-body camp just got its strongest evidence yet.