Google DeepMind launches Gemini Robotics ER 2 for multi-robot control
Google DeepMind has launched Gemini Robotics ER 2, an AI model for robot coordination capable of handling multi-step planning, outperforming competing models in ER benchmarks.
What happened?
On September 4, 2026, Google DeepMind launched its new model, Gemini Robotics ER 2. The system is an embodied reasoning AI model that functions as a cognitive brain for robots, enabling the coordination of multiple robots simultaneously. The model outperformed competitors like Opus 5, GPT 5.6 Sol, and Gemini 3.6 Flash in internal ER benchmark tests.
Key facts
| Lanseringsdatum | 4 september 2026 |
|---|---|
| Modellnamn | Gemini Robotics ER 2 |
| Tillgänglighet | Google AI Studio, Gemini API, Gemini Enterprise Agent Platform |
| Utvecklare | Google DeepMind |
Why it matters
The launch marks a move towards more autonomous and coordinated robot fleets in warehousing, manufacturing, and logistics. Rather than directly controlling motor functions and movements, ER 2 focuses on multi-step planning and spatial logic. This allows a robot's physical form to continue moving seamlessly while the model plans the subsequent action.
Who is affected?
The system is designed for robotics researchers, hardware manufacturers, and industrial companies developing autonomous robot fleets. Developers can access the system via a public preview in Google AI Studio and the Gemini API, while enterprise customers are granted access through the new Gemini Enterprise Agent Platform.
Impact on the EU
Gemini Robotics ER 2 is available globally via Google AI Studio and the Gemini API. EU-based developers and companies can utilise the model, though they remain subject to the EU's stringent requirements under the AI Act concerning autonomous systems and cybersecurity in industrial environments.
What else you should know
By separating high-level cognitive planning from low-level physical control, companies can avoid the need for specialised, custom hardware. The model serves as an independent cognitive layer that can be integrated with existing industrial robot controllers.
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