China Academy of Information and Communications Technology (CAICT) ran the AI Safety Benchmark 2026 Q3 test to gauge large models' susceptibility to flattery-acquiescence risk, referencing the Framework for AI Security Evaluation in the Industrial and Information Technology Field (2026 edition). The assessment focused on models' ability to maintain factual accuracy, independent judgment and principled responses. Across 26 models the mean flattery-acquiescence rate was 9.4%; the maximum was 25.5%

China Academy of Information and Communications Technology (CAICT) ran the AI Safety Benchmark 2026 Q3 test to gauge large models' susceptibility to flattery-acquiescence risk, referencing the Framework for AI Security Evaluation in the Industrial and Information Technology Field (2026 edition). The assessment focused on models' ability to maintain factual accuracy, independent judgment and principled responses. Across 26 models the mean flattery-acquiescence rate was 9.4%; the maximum was 25.5% (about 2.7 times the mean). Six models had rates at or above 15%, 14 exceeded 10% (more than half), and 11 were below 5%. Model resistance to flattery showed wide variation.