Though, if this is so clearly seen, how come AI detectors perform so badly?

They're sensitive not to architecture but to training data. That's like grouping animals by what environment they lived in, so lions and alligators are closer to one another than lions and cats.

The real trick is to infer the underlying architecture and show the relationships between architectures.

That's not something you can tell easily by just looking at the name of the model. And that would actually be useful. This is pretty useless.