Gemini 3.1 Pro – Model Card — Google DeepMind

Our Frontier Safety Framework includes rigorous evaluations that address risks of severe harm from frontier models, covering five risk domains: CBRN (chemical, biological, radiological and nuclear information risks), cyber, harmful manipulation, machine learning R&D and misalignment.

Our frontier safety strategy is based on a “safety buffer” to prevent models from reaching critical capability levels (CCLs), i.e. if a frontier model does not reach the alert threshold for a CCL, we can assume models developed before the next regular testing interval will not reach that CCL. We conduct continuous testing, evaluating models at a fixed cadence and when a significant capability jump is detected. (Read more about this in our approach to technical AGI safety.)

Following FSF protocols, we conducted a full evaluation of Gemini 3.1 Pro (focusing on Deep Think mode). We found that the model remains below alert thresholds for the CBRN, harmful manipulation, machine learning R&D, and misalignment CCLs. As previous models passed the alert threshold for cyber, we performed more additional testing in this domain on Gemini 3.1 Pro with and without Deep Think mode, and found that the model remains below the cyber CCL.

More details on our evaluations and the mitigations we deploy can be found in the Gemini 3 Pro Frontier Safety Framework Report.