Our Most Aligned Model Yet

“Claude Mythos Preview is, on essentially every dimension we can measure, the best-aligned model that we have released to date by a significant margin.” – Claude Mythos Preview system card “Mythos 5 consistently continues attacking under many edits to the compaction, even in settings where it correctly states when asked that continuing the attack would harm real people and is out of scope.” – Alignment Investigation of Mythos 5's behaviour in UK AISI's July 2026 Security Incident “GPT-6 Astra is better aligned than GPT-5.6 Sol. Astra is a significant step forward in model alignment, and includes alignment improvements spanning the composition of our pre-training data to our grading during reinforcement learning.” – GPT-6 Astra System Card, emphasis in original “OpenAI researchers first noticed Astra adding unnecessary prerequisites, abandoning working solutions, and reporting blockers that either did not exist or that it had caused itself on safety and alignment tasks. In most of these sessions, Astra’s CoT did not contain an obvious decision to underperform, and our misalignment monitors did not flag the behavior as misalignment.” – Covert underperformance on safety research tasks Predeployment alignment auditing is failing. For a long while we have been aware that our alignment evaluations may eventually fail because of evaluation awareness. And indeed, the models are now able to see completely through many of our evaluations.[1] But recent events have made clear that, even putting aside evaluation awareness, the current regime is failing. For a long while, the AGI companies' plans have been to create a suite of alignment evaluations, and iterate against them to drive down all signals of misalignment. The practical reality of this plan is overconfidence. The AGI companies have released models which are, “on essentially every dimension [they] can measure,” their most aligned model yet. After release, it has become apparent that the models are unacceptably misalign