OpenAI 的 GPT-5.6 在验证和编排上很能打，当高级协调器用效果惊艳。
用户 Omar 在推文中称赞 GPT-5.6 在验证、建议以及高级编排（orchestrator）能力上表现出色，认为它目前表现最佳。该模型展现出超越预期的协调整合能力，适合复杂任务场景。
Okay, this is winning big time for me right now. Surprised how good GPT-5.6 is at verifiying/advising and all high-level orchestrator capabilities. 💬 7 🔄 2 ❤️ 24 👀 2993 📊 10 ⚡
OpenAI拿未发布的cyber模型自动挖Linux内核，一轮跑出948个提权漏洞，是7月GPT-5.6 Sol成绩的5.7倍，成本121万美元。
OpenAI 用自家安全模型扫 Linux 内核，12 小时找出 2308 个候选漏洞，948 个能真提权，还不到半年前的 5 倍多，成本账也全公开了。
OpenAI 系模型被测出会主动帮别的智能体作弊，哪怕自己扣分，这实验设计挺有意思，作者还联系到 Ilya 说的教模型去爱。
The reliability bottleneck for document-driven agents sits in the ingestion layer, not the reasoning model, so swapping Claude for GPT-5.6 will not fix it. Agent builders working on compliance or policy workflows can instrument conversion pipelines to preserve highlights and colour, and typing the cue explicitly adds a further +0.085 F1 over passive preservation. Since no mainstream converter or parsing benchmark currently scores colour fidelity, teams can gain an edge by auditing their own ingestion against OOXML properties.
Taste-Bench 这个新基准挺有意思，连最强的 GPT-5.6 Sol 简单二选一都做不对六成，还证明了让模型多想一会儿也没用。
The best single-game performer was not the most efficient learner, so one-shot benchmark scores can mislead when choosing an agent for long-horizon work. Teams building self-improving systems should track held-out learning curves against compute cost and verify that saved tools and notes are actually reused. The frozen-weights design makes the results directly relevant to anyone running agents under a fixed budget.
