Google Releases Gemini Robotics 2.5, a Visual-Language-Action Model with Enhanced Capabilities for Industrial Applications
谷歌发布最强机器人模型 Gemini Robotics 2.5:不仅学会系蝴蝶结,更已在奔驰汽车生产线成功上岗
Google has released Gemini Robotics 2.5, its most capable visual-language-action robot model to date, which it claims can natively adapt to multiple robot hardware types and is currently open to Google's robot partners. The model reportedly completed over 200 complex tasks in testing, showing a 30% to 100% increase in task success rates and a 20% to 30% speedup versus a prior baseline. A proof-of-concept at a Mercedes-Benz plant in Germany demonstrated an actual operation success rate of 96% for humanoid robots performing parts picking and packing. Safety features include real-time physical hazard avoidance and an open-source jailbreak robustness benchmark (ASIMOV-Jailbreak) with a claimed resistance rate of 99.5%.
Source: Chinese robotics — Hardware and sensing · Read original article ↗
Article text · Machine translation into English
The fusion of artificial intelligence and physical robot technology has once again reached a milestone. Recently, Google officially released the most capable strongest Vision-Language-Action (VLA) robot model to date—Gemini Robotics 2.5. This model has achieved a comprehensive leap in three key areas: the breadth of robot skills, learning speed, and core dexterity, reliability, and safety. It is currently being fully opened to Google's robot partners.
Core performance has significantly leaped: task success rates have soared, and it natively adapts to multiple types of robots.
As a breakthrough achievement of the new generation, Gemini Robotics2.5 has completed rigorous testing of over 200 different complex tasks.
Test data shows that, compared to the previous generation baseline model, the success rate of this model in various tasks increased significantly by 30% to 100%, and the completion speed of executing tasks also accelerated by 20% to 30%. More importantly, this model possesses extremely strong versatility, capable of natively adapting to multiple different types of robot hardware carriers, demonstrating excellent cross-platform adaptability.
Mercedes production line field verification: Humanoid robots efficiently complete component picking and packing
To test its practical value in real industrial environments, Gemini Robotics2.5 has currently conducted a practical Proof of Concept (PoC) on the production line of the well-known German automaker Mercedes.
In a complex automobile manufacturing workshop site, the humanoid robot equipped with this model successfully undertook the tasks of picking and packing automobile parts, with an actual operation success rate as high as 96%. This striking data indicates that the model does not only remain at the theoretical stage in the laboratory but also possesses practical potential to handle industrial-grade high-intensity, high-precision operations.
Safety mechanisms fully upgraded: equipped with physical hazard avoidance, jailbreak resistance rate reaches 99.5%
In terms of safety and robustness, Gemini Robotics 2.5 also delivered an outstanding performance.
The model is equipped with an advanced real-time physical hazard avoidance mechanism at its base, which significantly improved the completion rate when the robot handles complex tasks involving safety. At the same time, to ensure the safety of the model in open environments, Google also open-sourced the jailbreak robustness testing benchmark ASIMOV-Jailbreak, whose measured jailbreak resistance rate reaches as high as 99.5%.
According to information, the rapid development and performance breakthroughs of Gemini Robotics 2.5 are largely attributed to the powerful acceleration in underlying computing power and reasoning capabilities of the new flagship large model Gemini 4Argon, which also laid a solid foundation for the subsequent development of embodied intelligence.
What the source reports
Publisher-reported claims, with original evidence. These results have not been independently verified by RoboSignal.
Reported numbers
tasks
>200
View original evidence
核心性能大幅跨越:任务成功率飙升,原生适配多类型机器人 作为新一代的突破性成果,Gemini Robotics2.5已经完成了超过200项不同复杂任务的严格测试。
Open source S5Reported success rate
96%
Reported trials
Reported success rate
30%
View original evidence
测试数据显示,相较于前代基线模型,该模型在各项任务中的成功率大幅提升了30% 至100%,执行任务的完成速度也加快了20% 至30%。
Open source S6Reported success rate
100%
View original evidence
测试数据显示,相较于前代基线模型,该模型在各项任务中的成功率大幅提升了30% 至100%,执行任务的完成速度也加快了20% 至30%。
Open source S6
- paper: not_reported
- code: not_reported
- weights: not_reported
- dataset: not_reported
What remains unknown
Not established in the collected evidence: Environment, Control, Data origin.
Reported performance applies to the described task. It does not establish general autonomy or deployment readiness.
Source excerpts and review record
Automatically extracted; no manual editorial approval recorded.
奔驰生产线实地验证:人形机器人高效完成零部件拣选打包 为了检验其在真实工业环境中的落地价值,Gemini Robotics2.5目前已在德国知名汽车制造商奔驰的生产线上开展了实际概念验证(PoC)。
Open source S8
核心性能大幅跨越:任务成功率飙升,原生适配多类型机器人 作为新一代的突破性成果,Gemini Robotics2.5已经完成了超过200项不同复杂任务的严格测试。
Open source S5
在复杂的汽车制造车间现场,搭载该模型的人形机器人成功承担了汽车零部件的拣选与打包任务,其实际操作成功率高达96%。
Open source S9
同时,为确保模型在开放环境中的安全性,谷歌还配套开源了越狱鲁棒性测试基准 ASIMOV-Jailbreak,其实测的越狱抵御率高达99.5%。
Open source S13
测试数据显示,相较于前代基线模型,该模型在各项任务中的成功率大幅提升了30% 至100%,执行任务的完成速度也加快了20% 至30%。
Open source S6
Source:Chinese robotics — Hardware and sensing · chinaz.com