I set it up as a joke, to make fun of all of the other benchmarks. To my surprise it ended up being a surprisingly good measure of the quality of the model for other tasks (up to a certain point at least), though I've never seen a convincing argument as to why.
I gave a talk about it last year: https://simonwillison.net/2025/Jun/6/six-months-in-llms/
It should not be treated as a serious benchmark.
What it has going for it is human interpretability.
Anyone can look and decide if it’s a good picture or not. But the numeric benchmarks don’t tell you much if you aren’t already familiar with that benchmark and how it’s constructed.
how can you say "it ended up being a surprisingly good measure of the quality of the model for other tasks" and also "It should not be treated as a serious benchmark" in the same comment?
if it is indeed a good measure of the quality of the model (hint: it's not) then, logically, it should be taken seriously.
this is, sadly, a great example of the kind of doublethink the "AI" hypesters (yes - whether you like it or not simon - that is what you are now) are all too capable of.