How do you decide which layers are the important ones?
sounds convincing, eh ... /s
On the less cynical note, approach does look interesting but I'd also like to understand how and why does it work, if it works at all.
For example in Phi 3 for example, the end of sentence token was wrong - if we use this, then our quants would be calibrated incorrectly, since chatting with the model will use the actual correct token.
Another is Llama 4 - https://github.com/ggml-org/llama.cpp/pull/12889 in which I fixed a RoPE issue - if we didn't fix it first, then again the calibration process would be incorrect.