DeepMind reveals Gemini Robotics 2.5 and open safety benchmark "ASIMOV-jailbreak"

Google DeepMind released Gemini Robotics 2.5, a vision-language-action model that achieved a 30 to 100 percent higher success rate and ran 20 to 30 percent faster than the previous version across more than 200 evaluated activities, the company said. In a partnership with Apptronik and Mercedes-Benz, Gemini-powered Apollo 2 humanoid robots kitted automotive parts in several European factories with a 96 percent success rate, and DeepMind also published an open safety benchmark called ASIMOV-jailbreak. DeepMind director Kanishka Rao said closing the remaining 4 percent gap to human-level reliability will be a "steep road.

Google DeepMind has revealed a new generation https://deepmind.google/blog/gemini-robotics-2-5-accelerates-real-world-physical-intelligence/ of the AI-powered Gemini Robotics platform. In the 2.5 release, Google says its robotic AI is getting tantalizingly close to completing real-world tasks as well as humans do. In fact, some Gemini robots were able to get actual work done in Mercedes-Benz factories, and the team is preparing for a day when robots operate alongside humans with an open source safety benchmark. DeepMind’s physical AI https://arstechnica.com/google/2025/09/google-deepmind-unveils-its-first-thinking-robotics-ai/ platform has several computational layers between user input and robotic action. There’s the vision-language model piece, which is Gemini Embodied Reasoning. Essentially, it takes your instructions and uses live video to plan how the robot can accomplish the task. The other main component is the vision-language-action VLA that actually generates robot actions, like moving an actuator—that’s Gemini Robotics, which has been bumped to version 2.5. DeepMind says that Gemini Robotics 2.5 is much better at tasks that require a high degree of dexterity. The model was evaluated across more than 200 activities, including serving food with tongs and using a pipette, as you would see in a laboratory. Google also showed that Apptronik’s Apollo 2 humanoid robot with Gemini Robotics 2.5 can now tie a bow with its five-fingered hands, a notable feat, because deformable objects like ribbon are notoriously difficult for robots to manipulate. Overall, Gemini Robotics 2.5 manages a 30 to 100 percent higher success rate compared to the last version https://arstechnica.com/ai/2026/07/google-reveals-gemini-robotics-2-0-promising-improved-dexterity-and-safety/ . It’s also 20 to 30 percent faster. But that’s based on laboratory testing. Google partnered with Apptronik and Mercedes-Benz to see how capable this AI is when faced with the uncertainty of the world outside robotics labs. The Gemini-powered Apollo 2 robots kitted automotive parts in a few European factories, reaching a 96 percent success rate. That’s an impressive showing compared to previous robotic AI systems, but it’s still probably not enough for a company like Mercedes-Benz. A human doing that sort of repetitive task will get it right virtually every time, and DeepMind director Kanishka Rao notes that closing that last 4 percent gap will be a “steep road.”