This is over a year old. The sky did not come down, everyone didn't switch to this in spite of the "advantages". If you look into why, you'll see that it does, in fact, affect the metrics, and some more than others, and there is no silver bullet.
The 2B4T model was literally released yesterday, and it's both smaller and better than what they had a year ago. Presumably the next step is that they get more funding for a larger model trained on even more data to see whether performance keeps improving. Of course the extreme quantization is always going to impact scores a bit, but if it lets you run models that otherwise wouldn't even fit into RAM, it's still worth it.
are you predicting, or is there already a documented finding somewhere?