This is precisely the wrong way to think about LLMs.

LLMs are never going to have fact retrieval as a strength. Transformer models don't store their training data: they are categorically incapable of telling you where a fact comes from. They also cannot escape the laws of information theory: storing information requires bits. Storing all the world's obscure information requires quite a lot of bits.

What we want out of LLMs is large context, strong reasoning and linguistic facility. Couple these with tool use and data retrieval, and you can start to build useful systems.

From this point of view, the more of a model's total weight footprint is dedicated to "fact storage", the less desirable it is.