Quantization publisher
NeveAI
NeveAI publishes 1 quantizations across 1 models in our index, averaging 4.313 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
1
Models covered
1
Avg effective bpw
4.313
across their files
Same model, same quant label, different bytes
largest disagreements first
| Model | Quant | NeveAI | vs | Theirs | Difference |
|---|---|---|---|---|---|
| Gemma-4-26B-A4B-StyleTune | IQ4_XS | 13.33 GiB | mradermacher | 13.46 GiB | -1.0% |
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-4-26B-A4B-StyleTune | 1 | 13.33 GiB |