IME big models just feel like big models. There's no training or RLing a small model that will encapsulate the "world knowledge" and minutia that a big model will glance from the same training data. So it makes perfect sense to use them where "big picture" is more important - planning, code review, process review (i.e. was what was asked implemented correctly?), etc.