I dunno, I never sense nerfs for local models, but consistently a few months after launch for corpo hosted models, seems odd my internal model for the capacity of a model drifts for anthropic models but not local ones. I've been using LLMs heavily even before ada/babbage/davinci days, and trust my internal calibration over baseless handwavey explanations for why im imagining things, especially when I have data that shows capacity regression on frontier models for tasks, e.g. one shot success at loss, 0 success in 15 attempts once nerf is sensed. Others publish their quantified capability regressions which are also more trust worthy than this kind of handwaving.
But if it is placebo, obviously he wouldn't notice any placebo change for local models, since he KNOWS he is using an immutable local model. That comparison only works if he doesn't know what model he is using.
I suppose you have a point, there is room for bias in perception and it could explain my sensed degradation of service, however, it doesnt explain the failure of tests, which isn't tied to my internal perception.
