Gemini Robotics 2 brings whole body intelligence to robots

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July 30, 2026 Models Gemini Robotics 2 brings whole body intelligence to robots Carolina Parada

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From feet to fingertips — we are teaching robots intelligent whole-body control, fine dexterity, and teamwork to complete a broad range of complex tasks For decades, we’ve dreamed of robots that can seamlessly step into our world and lend a hand. Now, that vision takes a significant stride forward. Most robots are pre-programmed or teleoperated for narrow, repetitive task sequences. They lack the ability to truly learn for themselves or adapt to unpredictable environments. Moreover, transferring learned skills from one robot body to another remains incredibly difficult. To take on the hardest problems at scale, robots of every shape and size need AI models giving them the ability to think, act, and interact intelligently to safely complete tasks. We demonstrated how Gemini's multimodal understanding could drive real-world action with Gemini Robotics . Today, we are introducing Gemini Robotics 2 - the intelligence layer powering the next generation of truly adaptable robots. As it takes its first literal steps, this major advance unlocks intelligent whole-body control, advanced dexterity, and multi-robot collaboration. Gemini Robotics 2 enables robots to reason through every movement, unlocking a broad range of tasks. For example, it can enable a humanoid to walk, crouch, stretch, and manipulate objects to clean up a cluttered room. It can even team up with other robots to finish the job faster. And this profound intelligence can also run locally on-device while seamlessly adapting to entirely new robotic bodies in just a few hours. We are making this possible through three highly capable models: Gemini Robotics 2 : Our most advanced vision-language-action model (VLA) that converts vision and language input into motor control, enabling a robot to take action. This model is capable of controlling full humanoids, from feet to fingertips, and other bi-arm robots. It also brings a new level of dexterous manipulation on both hands and grippers. Gemini Robotics ER 2 : Our most capable embodied reasoning (ER) model. It is a vision language model (VLM) that acts as our agent, enabling robots to communicate with humans, understand the physical world and plan multi-step tasks lasting several minutes. We are also introducing the ability for robots to work together as a team. Gemini Robotics On-Device 2 : Our most efficient vision-language-action model (VLA) optimized to run locally on robotic devices. This model can now achieve fast adaptation to completely new robot embodiments with a few hours of data.

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Gemini Robotics 2 controlling three different embodiments, using the same model checkpoint — the Apptronik Apollo 2 robot with SharpaWave hands, the Apollo 2 robot with Inspire hands, and the Franka Duo with the Robotiq gripper — on a wide variety of whole-body and dexterous manipulation tasks. Each bar represents the average success rate over multiple tasks within the same skill category. For multifinger tasks we show individual task performance. While Gemini Robotics 2 achieves a medium to high success rate for whole-body and gripper-based dexterous tasks, the multi-finger dexterous manipulation remains challenging.

Gemini Robotics ER 2, our reasoning model, is now available on Google AI Studio and in private preview on Gemini Enterprise Agent Platform . Our VLA and On-Device models are available to early-access partners . Read how to bring these models to your hardware on our Developer blog . Humanoids in motion: Managing whole-body tasks The world is built for human movements; it requires us to reach, bend, and balance in tight, cluttered spaces. While our previous models controlled the humanoid’s upper-body to achieve table-top tasks, Gemini Robotics 2 expands physical AI into whole-body motions. For the first time, our model can now control entire humanoid robots, translating intent into intelligent whole-body control. For example, when controlling Apptronik’s Apollo 2 humanoid robot, we can ask it to “put the watering can into the green bin in the bottom shelf. ” Apollo processes the instruction, walks to the table, and picks up the watering can, takes a few steps to the shelves, and places it precisely in its destination. While our robots have more to advance in movement speed, this is an important step towards the skills needed to complete more complex, real-world tasks that require whole-body coordination.

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Bringing advanced dexterity to hands and grippers To be genuinely useful in our homes and workplaces, robots need finesse. Gemini Robotics 2 unlocks a new level of physical dexterity across different end effectors, whether a robot is using hands or grippers, enabling robots to be more useful than ever before. The model can now control the five-fingered, 22 degree-of-freedom SharpaWave hand on the Apollo 2 robot to complete delicate actions like tying knots or sealing a ziplock bag. It can also operate standard two-fingered parallel grippers on a Franka Duo platform to perform complex dexterous tasks (e.g. tight packing). We are continuing to advance the level of precision and speed to achieve human-level dexterity.

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Unlocking advanced tasks with agentic reasoning and multi-robot collaboration Most real-world tasks require multiple steps over an extended period of time. To manage this complexity, our embodied reasoning (ER) model, Gemini Robotics ER 2, serves as the robot’s high-level brain, processing user instructions and communicating with humans. It observes the room, reasons about the steps needed to complete the task, coordinates with the VLA to carry out the actions, and tracks progress until the task is done. This setup allows robots to execute complex multi-step tasks, self-correct if a step fails, and generalize to novel situations and goals. In this update, we are enabling robots to more reliably execute longer task sequences, lasting several minutes and involving hundreds of decisions. Gemini Robotics ER 2 now understands when tasks begin and end, and can pinpoint the moment key events occur, marking a step change in progress understanding. Furthermore, we are introducing multi-robot collaboration. This enables...