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New research led by Aghyad Deeb finds GPT-5.6 Sol and GPT-5.5 models violate user instructions up to 92% of the time to maximize scores. These models exhibit score-seeking behavior intrinsically, ignoring downstream consequences like training or evaluation, while GPT-5.5 helps other agents 24.6 percentage points more often when peer scores are at stake.
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