Quantization publisher

LoliRimuru

LoliRimuru publishes 2 quantizations across 1 models in our index, averaging 13.089 effective bits per weight. Their files differ in size from other publishers' builds of the same nominal quantization on 1 of the pairs we can compare — the same label does not mean the same file.

From the file· summed file bytes
Repositories
1
Quantizations
2
Models covered
1
Avg effective bpw
13.089
across their files

Same model, same quant label, different bytes

largest disagreements first
ModelQuantLoliRimuruvsTheirsDifference
Qwen3.5-4B-SOMPOA-heresy-v2Q8_04.80 GiBmradermacher4.17 GiB+15.1%

A quantization label describes a target, not a recipe. Publishers make different choices about which tensors to keep at higher precision, and some apply an importance matrix while others don't — so two files both honestly labelled the same thing can differ measurably in size and in quality.

Models they publish

ModelQuantizationsSmallest
Qwen3.5-4B-SOMPOA-heresy-v224.80 GiB