I think this is because when you shrink it down, the model ends up space constrained and each “neuron” ends up having to do multiple duties. It can stil be tuned to perform well at specific tasks, but no longer generalizes as well. It’s somewhat unintuitive but models that are larger are often simpler than smaller ones for this same reason.