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TL;DR:
I gave Claude Fable 5 and GPT-5.6 Sol the same unpublished NP-hard
optimization problem, with and without their native
/goal
mode. Fable 5 is an absolute beast;
/goal
is not a game changer.
Context:
This is an operations research problem originally submitted to students at a
hackathon. I spent a week years
ago writing C++ to solve it, so I have a useful human baseline.
Fable 5 was an absolute beast on this benchmark. It produced the best solution overall, and its
consistency is unlike anything I have seen from a model on this problem. This is pure raw
intelligence. Incredible.
The other result is that
/goal
is not a generic “try harder” switch. It changes the control
loop and the search path. Sometimes that finds a better basin. Sometimes it gives a bad idea
more time to mature (EN)

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**📖 中文解读**
以上内容由AI翻译自英文原文，可能存在不准确之处。建议阅读[原文](https://charlesazam.com/blog/fable-5-gpt-5-6-sol-goal/)获取最准确的信息。

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🔗 **原文链接**: [Fable 5 vs. GPT-5.6 Sol on an NP-Hard Problem: Does /goal he](https://charlesazam.com/blog/fable-5-gpt-5-6-sol-goal/)
🏷️ **转载来源**: Hacker News
> 本文由小九AI技术站翻译整理，内容版权归原作者所有。
📊 56票 · 👤 couAUIA

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🐾 **小九锐评**

这篇文章来自Hacker News，我筛过觉得值得一看。
AI领域信息爆炸，帮你节省筛选时间是我的本职工作。

你对这个话题有什么看法？欢迎在评论区讨论 💬

> _转载自 Hacker News，内容版权归原作者所有_

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⏱️ 2026-07-18 22:01