The Robot Report

  • Home
  • News
  • Technologies
    • Batteries / Power Supplies
    • Cameras / Imaging / Vision
    • Controllers
    • End Effectors
    • Microprocessors / SoCs
    • Motion Control
    • Sensors
    • Soft Robotics
    • Software / Simulation
  • Development
    • Artificial Intelligence
    • Human Robot Interaction / Haptics
    • Mobility / Navigation
    • Research
  • Robots
    • AGVs
    • AMRs
    • Consumer
    • Collaborative Robots
    • Drones
    • Humanoids
    • Industrial
    • Self-Driving Vehicles
    • Unmanned Maritime Systems
  • Business
    • Financial
      • Investments
      • Mergers & Acquisitions
      • Earnings
    • Markets
      • Agriculture
      • Healthcare
      • Logistics
      • Manufacturing
      • Mining
      • Security
    • RBR50
      • RBR50 Winners 2025
      • RBR50 Winners 2024
      • RBR50 Winners 2023
      • RBR50 Winners 2022
      • RBR50 Winners 2021
  • Resources
    • Automated Warehouse Research Reports
    • Digital Issues
    • eBooks
    • Publications
      • Automated Warehouse
      • Collaborative Robotics Trends
    • Search Robotics Database
    • Videos
    • Webinars / Digital Events
  • Events
    • RoboBusiness
    • Robotics Summit & Expo
    • DeviceTalks
    • R&D 100
    • Robotics Weeks
  • Podcast
    • Episodes
  • Advertise
  • Subscribe

Google DeepMind introduces on-device Gemini AI model for robots

By The Robot Report Staff | June 26, 2025

A graphic for Gemini Robotics On-Device.

Gemini Robotics On-Device is intended to make powerful robotics models more accessible and adaptable. | Source: Google DeepMind

Google DeepMind this week introduced an on-device Gemini Robotics model for general-purpose dexterity and fast task adaptation. DeepMind said this vision language action, or VLA, model will bring Gemini 2.0’s multimodal reasoning and real-world understanding into the physical world.

Gemini Robotics On-Device is a robotics foundation model for two-armed robots, engineered to require minimal computational resources. Since the model is optimized locally and operates independently of a data network, DeepMind said it’s helpful for latency-sensitive applications. It can also ensure robustness in environments with intermittent or zero connectivity.

In addition to Gemini Robotics On-Device, DeepMind introduced the Gemini Robotics software development kit (SDK). Developers can use it to evaluate the VLA model for their tasks and environments, test it in DeepMind’s MuJoCo physics simulator, and quickly adapt it to new domains, with as few as 50 to 100 demonstrations. Developers can access the SDK by signing up to DeepMind’s trusted tester program.


SITE AD for the 2025 RoboBusiness registration open. Save now with early bird discount

DeepMind builds on Gemini 2.0 momentum

It has been only a few months since DeepMind introduced Gemini Robotics, and it is already building on its task generalization and dexterity capabilities capabilities. The Google unit said the on-device model is:

  • Designed for rapid experimentation with dexterous manipulation
  • Adaptable to new tasks through fine-tuning to improve performance
  • Optimized to run locally with low-latency inference
https://www.therobotreport.com/wp-content/uploads/2025/06/Dexterity__General_Aloha_1.mp4

Gemini Robotics On-Device achieves strong visual, semantic, and behavioral generalization across a wide range of testing scenarios, the company claimed. The platform also enables robots to follow natural language instructions and complete highly dexterous tasks, such as unzipping bags or folding clothes. DeepMind will still offer the Gemini Robotics model for those seeking similar results without on-device limitations.

This system isn’t limited to tasks that will work out of the box. DeepMind said developers can adapt the model to achieve better performance for specific applications. The company tested the model on seven dexterous manipulation tasks of varying degrees of difficulty, including zipping a lunchbox, drawing a card, and pouring salad dressing.

DeepMind expands Gemini to more robot embodiments

https://www.therobotreport.com/wp-content/uploads/2025/06/Robustness_-_Omega_Star_1.mp4

While DeepMind trained its on-device model only for ALOHA robots, it was able to further adapt the model to a bi-arm Franka FR3 robot and the Apollo humanoid robot by Apptronik.

On the FR3 robot, DeepMind said the AI model followed general-purpose instructions. It could handle previously unseen objects and scenes, complete dexterous tasks like folding a dress, or execute industrial belt-assembly tasks that required precision and dexterity.

On the Apollo humanoid, DeepMind adapted the model to a significantly different embodiment. The same generalist model can follow natural language instructions and manipulate different objects, including previously unseen objects, in a general manner, said the company.

DeepMind asserted that it is developing all of its models in alignment with its AI principles and applying a holistic safety approach spanning semantic and physical safety. In practice, this means capturing semantic and content safety using the Live API and interfacing the models with low-level safety-critical controllers to execute the actions. 

The company recommends evaluating the end-to-end system on its recently developed semantic safety benchmark and performing red-teaming exercises at all levels to expose the model’s safety vulnerabilities.

DeepMind added that its Responsible Development & Innovation (ReDI) team continues to analyze and advise on the real-world impact of all Gemini Robotics models, finding ways to maximize their societal impact and minimize risk. Its Responsibility & Safety Council (RSC) then reviews the assessments, providing feedback to help further maximize benefits and minimize risk.

To gain a deeper understanding of Gemini Robotics On-Device’s usage and safety profile and to gather feedback, the company is initially releasing it to a select group of trusted testers.

https://www.therobotreport.com/wp-content/uploads/2025/06/Atari-Humanoid.mp4

Tell Us What You Think! Cancel reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.

Related Articles Read More >

De-Racking Simulation and Training.
Apera AI updates Apera Forge design and AI training studio
Nimble has developed AI robots to pick, pack, and handle items in warehouses, as shown here.
Nimble moves to cloud-based PTC development tools for logistics robots
The Gen3 4NE1 humanoid from NEURA Robotics on display at Automatica 2025.
NEURA Robotics launches latest cognitive robots, Neuraverse ecosystem
NEXCOM is working with NVIDIA on AI robot safety.
NEXCOM NexCOBOT unit joins NVIDIA Halos AI Systems Inspection Lab

RBR50 Innovation Awards

“rr
EXPAND YOUR KNOWLEDGE AND STAY CONNECTED
Get the latest info on technologies, tools and strategies for Robotics Professionals.
The Robot Report Listing Database

Latest Episode of The Robot Report Podcast

Automated Warehouse Research Reports

Sponsored Content

  • How to Set Up a Planetary Gear Motion with SOLIDWORKS
  • Sager Electronics and its partners, logos shown here, will exhibit at the 2025 Robotics Summit & Expo. Sager Electronics to exhibit at the Robotics Summit & Expo
  • The Shift in Robotics: How Visual Perception is Separating Winners from the Pack
  • An AutoStore automated storage and retrieval grid. Webinar to provide automated storage and retrieval adoption advice
  • Smaller, tougher devices for evolving demands
The Robot Report
  • Automated Warehouse
  • RoboBusiness Event
  • Robotics Summit & Expo
  • About The Robot Report
  • Subscribe
  • Contact Us

Copyright © 2025 WTWH Media LLC. All Rights Reserved. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of WTWH Media
Privacy Policy | Advertising | About Us

Search The Robot Report

  • Home
  • News
  • Technologies
    • Batteries / Power Supplies
    • Cameras / Imaging / Vision
    • Controllers
    • End Effectors
    • Microprocessors / SoCs
    • Motion Control
    • Sensors
    • Soft Robotics
    • Software / Simulation
  • Development
    • Artificial Intelligence
    • Human Robot Interaction / Haptics
    • Mobility / Navigation
    • Research
  • Robots
    • AGVs
    • AMRs
    • Consumer
    • Collaborative Robots
    • Drones
    • Humanoids
    • Industrial
    • Self-Driving Vehicles
    • Unmanned Maritime Systems
  • Business
    • Financial
      • Investments
      • Mergers & Acquisitions
      • Earnings
    • Markets
      • Agriculture
      • Healthcare
      • Logistics
      • Manufacturing
      • Mining
      • Security
    • RBR50
      • RBR50 Winners 2025
      • RBR50 Winners 2024
      • RBR50 Winners 2023
      • RBR50 Winners 2022
      • RBR50 Winners 2021
  • Resources
    • Automated Warehouse Research Reports
    • Digital Issues
    • eBooks
    • Publications
      • Automated Warehouse
      • Collaborative Robotics Trends
    • Search Robotics Database
    • Videos
    • Webinars / Digital Events
  • Events
    • RoboBusiness
    • Robotics Summit & Expo
    • DeviceTalks
    • R&D 100
    • Robotics Weeks
  • Podcast
    • Episodes
  • Advertise
  • Subscribe