The issue is that they claim that you don't need an extensive amount of data to do efficient reasoning. But that alone is a bit misleading, if you need a massive model to fine tune and another one to piece together the small amount of data.

I've seen the textbook analogy used, but to me it's like a very knowledgeable person reading an advanced textbook to become an expert. Then they say they're better than the other very knowledgeable persons because he read that manual, and everyone can start from scratch using it.

So there's nothing wrong with making a more efficient model from an existing one, the issue is concluding you don't need all the data that made the existing one possible in the first place. While that may be true, this is not how you prove it.