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We run our evaluations on current frontier models and find that none of them show concerning levels of either situational awareness or stealth. We do not find evidence of strong dangerous capabilities in the models we evaluated, but we flag early warning signs Our goal is to help lay the groundwork for a rigorous science of dangerous capability evaluation, in preparation for future, more capable models. Evaluating frontier models for stealth and situational awareness published 5/4/2025 by mary phuong, roland s Zimmermann, ziyue wang, david lindner, victoria krakovna, sarah cogan, allan dafoe and 2 more. Additional results in technical paper 'evaluating frontier models for stealth and situational awareness' (45 pages) [arxiv, 2025] We argue that models would need a certain level of stealth ability and situational awareness to cause harm via scheming Our evaluation results show that current models do not yet reach the requisite level of either capability. Our paper “ evaluating frontier models for stealth and situational awareness ” focuses on an empirical assessment of the component capabilities for ai scheming. Evaluating frontier models for stealth and situational awareness Such behavior could be very hard to detect, and if present in future advanced systems, could pose severe loss of control risk We run our evaluations on current frontier models and find that none of them show concerning levels of either situational awareness or stealth We published “evaluating frontier models for stealth and situational awareness” describing our scheming capability evaluations Also see the blogpost putting this work into context of our approach to evaluating and mitigating risks from deceptive alignment. A new frontier for world models august 2025 models learn more chevron_right A recent study highlights the potential risks associated with frontier ai models that may pursue covert objectives misaligned with developer intentions This article delves into the evaluations designed to measure ai's stealth and situational awareness, shedding light on the implications for ai safety and deployment.