I really had high hopes for the larger Ternary Bonsai and it feels like there is scope to improve, but I get the sense (albeit a naïve, probably not fully informed sense) that improvement can perhaps only come by training directly into ternary.
Whaaat, a 27b model might be better than 9b or 12b model? What would make you do such an outrageous claim?
It also had some issues that might be parsing/chat template stuff, tool calling oddities. I will try it again, I did try it pretty much the day it shipped and it's possible there are more improvements in their llama.cpp fork since.
It would be churlish to be overcritical, mind you — the PrismML ternary stuff is an advance — but it feels like it should be applied at training. I figure we will see that, somewhere, quite soon.
Did you try the BottleCap ThinkingCap Qwen post-train with the reduced thinking overhead?
I think it does use fewer tokens while reasoning, which is potentially useful. I need to do more testing, because any performance advantage over the 27B is useful for me on an M1 Max.