General robot control
Controls robots of different shapes and sizes, from tabletop systems to full humanoids, so the same model can scale across embodiments.
Gemini Robotics 2
Gemini Robotics 2 is Google DeepMind's robotics model family for whole-body control, dexterous manipulation, and task reasoning across different robot embodiments. It includes an on-device option for local execution and adaptation when connectivity or latency is a constraint.
Overview
Gemini Robotics 2 is Google DeepMind's robotics model family for physical AI. The announcement centers on three models: Gemini Robotics 2 for vision-language-action control, Gemini Robotics ER 2 for embodied reasoning, and Gemini Robotics On-Device 2 for local execution on robotic hardware.
The system is intended to help robots perceive instructions, reason about tasks, and interact with the physical world across a broad range of embodiments. The source shows use on humanoids, bi-arm robots, hands, and grippers, with examples that include whole-body movement, dexterous object handling, and collaboration between robots.
Capabilities
Vision-language-action control
Translates vision and language input into motor actions, enabling a robot to act on instructions in the physical world.
Whole-body coordination
Extends control to whole-body motion on humanoid robots, including stepping, squatting, bending, and balancing in cluttered spaces.
Dexterous manipulation
Supports dexterous manipulation with hands and grippers, including five-finger, 22-degree-of-freedom hands and standard two-finger grippers.
Multi-step task planning
Uses an embodied reasoning model to plan multi-step tasks, communicate with humans, and track progress over several minutes.
Local deployment and adaptation
Includes an on-device model optimized for local execution and fast adaptation to new robot embodiments with a few hours of data.
Use Cases
Whole-body household or workspace tasks
A humanoid robot can follow a task that requires walking to an object, crouching or bending to reach it, and placing it in a target location in a cluttered room.
Dexterous object handling
A robot with a five-finger hand or parallel gripper can perform delicate manipulation such as tying knots, sealing a ziplock bag, or packing tightly into a container.
Long-horizon task execution
A reasoning layer can break a multi-step instruction into smaller actions, monitor progress, and recover when a step fails during longer tasks.
Multi-robot collaboration
Multiple robots can coordinate on a shared workflow when a single robot cannot complete the job alone, using the reasoning model to organize collaboration.
Local robotics deployment
A robot platform that must run without internet connectivity or low-latency cloud access can use the on-device model for local control and adaptation.
Pros and Cons
Pros
- Covers a broad set of robot embodiments, including tabletop systems, bi-arm robots, humanoids, hands, and grippers.
- Combines control and reasoning models so robots can plan, act, and track longer task sequences.
- Supports whole-body motion that is more suitable for cluttered, human-built environments than static arm-only control.
- Includes an on-device option for local execution when latency or connectivity are constraints.
Cons
- The source says whole-body motion is still moving toward higher speed and more advanced manipulation remains challenging, especially for multi-finger dexterous tasks.
- The public information is incomplete on integrations, deployment details, and general availability beyond early-access and preview access.
FAQ
What is the difference between Gemini Robotics 2, ER 2, and On-Device 2?
Gemini Robotics 2 is a vision-language-action model for robot control. Gemini Robotics ER 2 is the embodied reasoning model that plans multi-step tasks and communicates with humans, while Gemini Robotics On-Device 2 is the local, efficient VLA model for running on robotic hardware without relying on network latency or internet connectivity.
How is Gemini Robotics 2 made available?
Google DeepMind says Gemini Robotics ER 2 is available on Google AI Studio and in private preview on Gemini Enterprise Agent Platform. The VLA and On-Device models are available to early-access partners.
What kinds of robots can it control?
The page describes Gemini Robotics 2 as a model for whole-body control and dexterous manipulation on robots ranging from tabletop robots to full humanoids and bi-arm systems.
What kinds of tasks does it support?
The announcement highlights whole-body movements such as walking, crouching, stretching, balancing, and manipulating objects, as well as dexterous actions with hands and grippers like tying knots, sealing a ziplock bag, and tight packing.
When would the on-device model be useful?
The source says the on-device model is designed for cases that need to run locally, including situations without network latency or internet connectivity. It can adapt to new robot embodiments with a few hours of data.
Quick Facts
- Category
- World models & physical AI
- Product family
- Gemini Robotics 2
- Source domain
- deepmind.google
- Primary model types
- VLA, embodied reasoning (VLM), on-device VLA
- Availability
- ER 2 on Google AI Studio and private preview in Gemini Enterprise Agent Platform; VLA and On-Device to early-access partners
- Typical robot forms
- Tabletop robots, bi-arm robots, humanoids, hands, grippers
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