Quantization publisher

Handyfff

Handyfff publishes 7 quantizations across 1 models in our index, averaging 5.978 effective bits per weight. Their files differ in size from other publishers' builds of the same nominal quantization on 8 of the pairs we can compare — the same label does not mean the same file.

From the file· summed file bytes
Repositories
1
Quantizations
7
Models covered
1
Avg effective bpw
5.978
across their files

Same model, same quant label, different bytes

largest disagreements first
ModelQuantHandyfffvsTheirsDifference
gemma-4-E2B-it-uncensoredQ8_03.99 GiBmradermacher4.63 GiB-13.7%
gemma-4-E2B-it-uncensoredQ8_03.99 GiBTrevorJS4.63 GiB-13.7%
gemma-4-E2B-it-uncensoredQ3_K_M2.49 GiBmradermacher2.98 GiB-16.4%
gemma-4-E2B-it-uncensoredQ4_K_M2.70 GiBmradermacher3.19 GiB-15.3%
gemma-4-E2B-it-uncensoredQ5_K_M2.89 GiBmradermacher3.38 GiB-14.4%
gemma-4-E2B-it-uncensoredQ6_K3.09 GiBmradermacher3.58 GiB-13.6%
gemma-4-E2B-it-uncensoredQ2_K2.30 GiBmradermacher2.78 GiB-17.5%
gemma-4-E2B-it-uncensoredQ4_K_M2.70 GiBTrevorJS3.19 GiB-15.3%

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
gemma-4-E2B-it-uncensored72.30 GiB