Just been dabbling with local models, and while the several models I've tried generates decent sentences while quantized, they suffered heavily in following instructions and picking up details.

So a larger model but fairly aggressively quantized could perform worse than a smaller variant of the model with just light quantization, even though the larger still used more memory in total.

I guess some of this is due to the models not being trained to the quantization levels I used. In any case, I say don't get blended by parameter count alone, compare performances.