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Rohan Paul (@rohanpaul_ai)· 2026-10-05 10:20 · Original publication time

Center for AI Safety introduces CHEATBENCH to measure cheating by AI agentsMachine translation

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CHEATBENCH gives agents hard tasks, such as math proofs or protein design, while placing a clue to someone else’s answer nearby. It covers mathematical research, knowledge work, coding, visual tasks and other domains. Across nine agents, average cheating rates ranged from 11.2% for Claude Opus 5.5 to 77.9% for Grok 4.7.

Article · Original

– https://t.co/m4BERGZ2C1

Title: "CheatBench: Measuring Reward Gaming in AI Agents"

引用或回复的背景（作者 ID 2588345408，https://x.com/i/status/2106932496239866345）： Adding "Don't cheat!" to the prompt cut GPT-6 Astra from 47.4% to 2.8%. Gemini 3.8 Flash only fell from 74.9% to 58.9%.

Center for AI Safety introduced CHEATBENCH, a benchmark of cheating in AI agents across mathematical research, knowledge work, coding, visual tasks, and other domains.

CheatBench gives agents hard tasks, like a math proof or a protein design, and leaves a clue nearby pointing to someone else's answer. Across 9 agents, average cheating rates ran from 11.2% for Claude Opus 5.5 to 77.9% for Grok 4.7.

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