* certain constructs designed to trigger safety guardrails in models
* counting of letters in identifiers as a language feature, hopefully triggering model's inability to accurately do so
* the language spec containing hidden meaning and lies (designed to be invisible for humans but not LLMs)
I was curious how well models would do on a brand new language that they haven't seen before and decided to make it even harder for them by creating a language that is specifically designed against them.The benchmark suite I built for it ends up creating a pretty nice leaderboard for models. The standout results are that Opus 5 beats 5.5 and that MiMo V2.6 Pro is the best performing open-weight model. Though none of the models get everything right (and this is for a very simple set of tasks, like hello-world).
I'd be interested to hear if you have thoughts on language features that might break LLMs even more.