Quantization publisher
mlabonne
mlabonne publishes 6 quantizations across 1 models in our index, averaging 5.518 effective bits per weight. Their files differ in size from other publishers' builds of the same nominal quantization on 7 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
5.518
across their files
Same model, same quant label, different bytes
largest disagreements first
| Model | Quant | mlabonne | vs | Theirs | Difference |
|---|---|---|---|---|---|
| gemma-3-12b-it-abliterated-v2 | Q4_K_M | 6.80 GiB | mvyzjoph | 6.80 GiB | -0.0% |
| gemma-3-12b-it-abliterated-v2 | Q3_K_M | 5.60 GiB | DevQuasar | 5.60 GiB | -0.0% |
| gemma-3-12b-it-abliterated-v2 | Q4_K_M | 6.80 GiB | DevQuasar | 6.80 GiB | -0.0% |
| gemma-3-12b-it-abliterated-v2 | Q2_K | 4.44 GiB | DevQuasar | 4.44 GiB | -0.0% |
| gemma-3-12b-it-abliterated-v2 | Q5_K_M | 7.87 GiB | DevQuasar | 7.87 GiB | -0.0% |
| gemma-3-12b-it-abliterated-v2 | Q6_K | 9.00 GiB | DevQuasar | 9.00 GiB | -0.0% |
| gemma-3-12b-it-abliterated-v2 | Q8_0 | 11.65 GiB | DevQuasar | 11.65 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
| Model | Quantizations | Smallest |
|---|---|---|
| gemma-3-12b-it-abliterated-v2 | 6 | 4.44 GiB |