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Gemini Robotics 2

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Gemini Robotics 2 is a system of three AI models released by Google DeepMind that enables robots to perform complex multi-step physical tasks with full-body control, fine motor dexterity, and multi-robot coordination. The system can control different robot embodiments including humanoid robots like the Apptronik Apollo 2, adapting skills across different platforms with minimal training examples and running lightweight versions on-device without internet connectivity. Success rates range from 32% to 92% depending on task complexity, enabling robots to handle real-world tasks involving whole-body movements, manipulation, and collaborative coordination.

Updated 3 August 2026

Specifications

No specifications recorded yet.

Latest developments

The Sequence Radar #906: Last Week in AI: Open Models, Intelligent Robots, and the Price of Conviction TheSequence · 1 day ago · 22

Gemini Robotics 2 brings us one step closer to physical AGI The New Stack · 2 days ago · 7

OpenAI cuts Luna API prices 80% and launches faster Sol inference The Neuron · 3 days ago · 42

Google DeepMind Ships Three Physical AI Models For Whole Body Control, Dexterity And Multi Robot Collaboration MarkTechPost · 3 days ago · 35

Google DeepMind’s new AI model can control a robot’s entire body The Verge · 4 days ago · 27

Gemini Robotics 2 brings whole body intelligence to robots Google DeepMind · 6 days ago · 23

Timeline

Month Quarter Year

Q3 2026

Multiple AI companies release competitive open-weight models as industry trend shifts toward openness Open source release

OpenAI releases GPT-5.6 model family with efficiency improvements and significant price reductions Model release

Google DeepMind releases Gemini Robotics 2, a suite of AI models enabling whole-body robot control, dexterity, and multi-robot collaboration Model release

Relationships

Products & technology

Google DeepMind develops this model · 5 sources
Integrated with Apptronik Apollo 2 · 1 source
Integrated with Franka Duo · 1 source
Google develops this model · 1 source
Apollo 2 integrated with this model · 1 source

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TLDRocket 3 August 2026

Open-source AI models are consolidating their foothold as the dominant deployment pattern, even as frontier capabilities remain concentrated at a handful of well-funded labs. Interconnects launched the Artifacts Hub and Adoption Dashboard to track 792 open-weight models released in two years, mapping adoption by geography and revealing how deeply DeepSeek and Chinese models have penetrated deployment pipelines globally. Meanwhile, DeepSeek itself proved that scale isn't everything: its V4-Flash model, a leaner 284-billion-parameter variant, outperformed its own flagship on agent benchmarks through careful post-training. The MIT-licensed release lets enterprises avoid vendor lock-in entirely, directly controlling deployment and retraining at lower infrastructure cost.

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