Quantization publisher

hiratagoh

hiratagoh publishes 6 quantizations across 1 models in our index, averaging 7.912 effective bits per weight. Their files differ in size from other publishers' builds of the same nominal quantization on 3 of the pairs we can compare — the same label does not mean the same file.

From the file· summed file bytes
Repositories
1
Quantizations
6
Models covered
1
Avg effective bpw
7.912
across their files

Same model, same quant label, different bytes

largest disagreements first
ModelQuanthiratagohvsTheirsDifference
llm-jp-4-32b-a3b-thinkingQ4_K_M19.93 GiBash281320.04 GiB-0.6%
llm-jp-4-32b-a3b-thinkingQ4_K_M19.93 GiBmmnga-o19.93 GiB0.0%
llm-jp-4-32b-a3b-thinkingQ5_K_M22.73 GiBmmnga-o22.73 GiB0.0%

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
llm-jp-4-32b-a3b-thinking616.37 GiB