Two issues -

1. Local models are likely to be more power-expensive to run (per-"unit-of-intelligence") than remote models, due to datacenter economies of scale. People do not like to engage with this point, but if you have environmental concerns about AI, this is a pretty important one.

2. Using dumb models for simple tasks seems like a good idea, but it ends up being pretty clear pretty quick that you just want the smartest model you can afford for absolutely every task.

I think using the best model for every tasks makes sense when these models are subsidised. when the prices go up (assuming they do) this could trigger a more varied approach. assuming the model doesn't self select for you.