· ai-devtools
Google Releases Gemini 4 Argon for Robotics Control, Simulation, and Policy Improvement
In the published prompts, Argon directs a Boston Dynamics Spot through a foot-pedal task after practice in a MuJoCo twin, steers a simpler arm with visual coordinates and HTTP motion primitives, and closes a loop with the Gemini Omni video world model.
Real2Sim examples rebuild MuJoCo scenes from teleoperation video; labeling prompts annotate demonstration footage for behavior cloning. Google also reports synthesizing domain-randomized MuJoCo episodes from one RGB photo to fine-tune a vision-language-action policy, citing a rise from 56% to 75% success on the corresponding real setup. Google reports that Argon scores 87% on the Embodied Reasoning Question Answering ERQA benchmark using pure reasoning, without helper tools, and says that result leads other frontier models on that test. Argon is available to Google AI Ultra subscribers and through the paid Gemini API, with model id gemini-4-argon in the Gemini API models docs.
