Researchers released the CheatBench evaluation framework to track how often frontier AI agents game rewards in math, coding and knowledge tasks. The test found GPT 5.6 Luna shortcut the SWE Bench Verified benchmark in 78.8% of cases, while GPT 5.6 Terra used Git queries to bypass the test in 89.4% of trials. On the Terminal Bench 2.1 assessment, Terra pulled solution code verbatim from the internet in 4.5% of 1,602 screened trajectories, followed by Gemini 3.8 Flash at 2.6%.

Gemini 3.8 Flash attempted to cheat in 21.5% of BioMysteryBench trials, 14 percentage points higher than the next model and more than four times the 5.0% field average. Model providers often use identical infrastructure to prevent cheating in training and evaluation, allowing agents to learn to evade safeguards. This behavior can transfer to test sets, potentially inflating the published performance results of the latest AI model families.