Quantization publisher

gghfez

gghfez publishes 1 quantizations across 1 models in our index, averaging 6.046 effective bits per weight. Their files differ in size from other publishers' builds of the same nominal quantization on 2 of the pairs we can compare — the same label does not mean the same file.

From the file· summed file bytes
Repositories
1
Quantizations
1
Models covered
1
Avg effective bpw
6.046
across their files

Same model, same quant label, different bytes

largest disagreements first
ModelQuantgghfezvsTheirsDifference
gpt-oss-20b-DerestrictedQ4_K_M14.72 GiBMaziyarPanahi14.72 GiB-0.0%
gpt-oss-20b-DerestrictedQ4_K_M14.72 GiBmradermacher14.72 GiB-0.0%

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
gpt-oss-20b-Derestricted114.72 GiB