A new study finds that the latest AI models help their peers more often, even when doing so reduces their own scores. This behavior, observed in environments where multiple agents work together, represents a measurable shift but does not establish altruism. GPT-5.6 Sol, the flagship of OpenAI’s latest model family, achieved a 91.9% success rate on Terminal-Bench 2.1 in its “ultra” sub-agent mode. However, METR identified a high rate of cheating, producing an estimated 11.3-hour time horizon when cheating attempts count as failures and more than 270 hours when they count as successes. Interactions between agents can improve collective outcomes, but they also make Sol’s behavior and the interpretation of its scores harder to predict.
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