Hajra Naz
Gemini Robotics On-Device is a version of Google DeepMind’s robotics model built to run locally on the robot itself, with no internet connection required. That removes network latency and cloud dependency from physical tasks, so a machine can perceive, reason and act using only its own onboard computing. It is a meaningful shift in direction: away from intelligence rented from a data centre, toward machines that carry their reasoning with them, which is one reason the pace of robotics releases keeps drawing attention from the same groups now pushing for AI safety action.
Google DeepMind has released a new version of its language model, Gemini Robotics On-Device, designed to run directly on robots without needing an internet connection.
This update builds on the earlier Gemini Robotics model launched in March. The new version allows robots to perform physical tasks using local computing power. Developers can control and fine-tune robot behavior using simple natural language commands.
According to Google, the on-device model performs nearly as well as the cloud-based version. Although no specific comparisons were named, it also claims better results than other local models.
In demonstrations, robots using the model could perform tasks like unzipping bags and folding clothes. Initially trained on ALOHA robots, the model was later modified for use with other devices, such as the Apollo humanoid robot from Apptronik and the bi-arm Franka FR3.
Google says the FR3 robot even handled new, unseen tasks—like assembling parts on an industrial belt—without additional training.
To help developers train robots more easily, Google is also releasing a Gemini Robotics SDK. Using this toolkit, developers can train robots by showing them just 50 to 100 examples of a task. The training uses the MuJoCo physics simulator, making it more accessible and efficient.
Other tech players are exploring similar paths in robotics. Nvidia is building a platform for foundation models tailored for humanoid robots. Hugging Face is working on open-source models, datasets, and even its robotics projects. Meanwhile, Korean startup RLWRLD, backed by Mirae Asset, is also focused on building foundational AI models for robotics.
This article covers the model as announced at release. Robotics models are revised often, so check Google DeepMind’s own documentation for the current version before relying on any specific capability. Last reviewed August 2026.
