Models New
Google DeepMind introduces Gemini Robotics 2.5 and reports a 96% success rate picking car parts on Mercedes-Benz lines
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Google DeepMind introduced Gemini Robotics 2.5, which it calls its most capable vision-language-action model to date: a model that turns camera input and instructions into robot movements. It is rolling out to DeepMind's robotics partners, not as a public API.
DeepMind says it evaluated the model on more than 200 tasks, such as serving food with tongs, tying a bow and pipetting liquid, and that it reaches a 30% to 100% higher success rate than earlier baselines, depending on the task, while finishing tasks 20% to 30% faster.
In a proof of concept with Apptronik and Mercedes-Benz, Apptronik's Apollo 2 humanoid sorted metal brackets from bulk bins into sequencing trays on production lines in Kecskemét, Hungary, and Sindelfingen, Germany, with a 96% success rate, according to DeepMind. The company also says new safety guidance raised safe task completion around obstacles by 33% and around nearby people by 43%.
Caveat. All figures are DeepMind's own evaluations; no independent results were found. The page is dated 10 November, while DeepMind's news feed timestamps the post at 20:51 Paris time on 9 November; no earlier edition carried it.
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