Google DeepMind releases Gemini Robotics 2, which combines several different AI models into a single system to control a range of robots, including humanoids
The latest version of Google DeepMind's AI model includes a significant jump into “physical AGI.” But plopping AI into the real world comes with risks.
WiredWill Knight
Context & Ripple Effects
Gemini Robotics 2 follows DeepMind’s progression from separate Gemini-based robotics and embodied-reasoning models to 1.5 models for multi-step robotic work and then stronger spatial and physical reasoning in Robotics-ER 1.6. The new release matters because it presents those capabilities as one control system across robot types, including humanoids.
The arc also includes an on-device model and SDK intended to help robots adapt to new tasks, alongside Boston Dynamics’ integration of Gemini Robotics into Atlas. That makes the question less about a single model demonstration and more about how broadly a common AI layer can be used in physical machines.
First-order effects
Google DeepMind now offers a unified Gemini Robotics 2 system for controlling multiple robot forms, rather than positioning distinct models around narrower robotics functions.
Robot makers and developers evaluating Gemini gain a single integration target, while deployments face the immediate safety and reliability constraints of placing AI-driven behavior in real environments.
Second-order effects
Humanoid and other robotics vendors will be pressured to show that their own control stacks can match a general-purpose, multi-model system or can integrate with it effectively.
Integrators must place more emphasis on testing, monitoring, and task-specific safeguards as model capability moves from reasoning about physical space to controlling physical actions.
Third-order effects
If unified control models prove reusable across hardware, the robotics market could shift toward a layered structure: foundation-model providers supply the intelligence layer while manufacturers differentiate through hardware, data, and deployment expertise.
The same consolidation would make operational AI governance more central, since failures or unsafe behavior in a common control layer could propagate across many types of machines.
The trend: Robotics AI is moving from specialized models toward reusable, general-purpose control layers that connect foundation-model capabilities to heterogeneous physical hardware.
Introducing Gemini Robotics 2: the next era of truly adaptable robots from @GoogleDeepMind 🤖 Powered by three new models, it brings whole-body control, fine dexterity, and teamwork to complex tasks — making robots more helpful in the real world. [video]
🤖✨ Gemini Robotics ER 2 gives you the spatial and reasoning capabilities of massive frontier models (like Opus 5 and GPT 5.6 Sol), but with the sub-second latency and cost efficiency required to actually run continuous video feeds on physical robots in the real world. So excited …
Huge congrats to the @GoogleDeepMind team on launching Gemini Robotics 2! Watching Apollo 2 use advanced reasoning to navigate whole-body tasks and fine-tuned dexterity is a massive leap forward. See it for yourself! 👇 #apptronik #robotics #AI #humanoids
One brain. For any robot. 🤖 We're launching Gemini Robotics 2: our next-generation physical AI bringing full body intelligence to humanoids, advanced dexterity, multi-robot teamwork and more.
Gemini Robotics 2 is here, with our new suite of models, robots can now reason through every movement to manage tasks that weren't possible before, like tying delicate knots - and even team up to solve complex workflows. Huge congrats to the robotics team on this great milestone!
Three new models power this breakthrough: 1️⃣ Gemini Robotics 2: A vision-language-action model controlling humanoids from feet to fingertips 2️⃣ Gemini Robotics ER 2: Capable of real-world video understanding and complex, multi-step planning 3️⃣ On-Device 2: Runs locally and ada…
Meet Gemini Robotics 2: our next-generation physical AI from @GoogleDeepMind that gives robots the ability to think, reason, act, and even work together.
Gemini Robotics 2 moves physical AI beyond tabletop tasks, enabling intelligent whole-body control for humanoids. Watch @Apptronik's Apollo 2 process a single prompt to reach, bend, and pick up a watering can ↓ [video]
Introducing Gemini Robotics ER 2, our latest robotics embodied reasoning model based on Gemini. So much progress from our last ER model (and baseline Gemini 3.6 Flash). Very excited to see more robots do useful things with this model! [image]
Google DeepMind just introduced Gemini Robotics 2. It's a single VLA that unlocks physical dexterity across different end effectors, hands or grippers, from one model checkpoint. Apptronik's Apollo 2 humanoid, with the 22-DoF SharpaWave hand, ties knots and seals a ziplock bag [v…