Quantization publisher
hungng
hungng publishes 1 quantizations across 1 models in our index, averaging 14.270 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
14.270
across their files
Same model, same quant label, different bytes
largest disagreements first
| Model | Quant | hungng | vs | Theirs | Difference |
|---|---|---|---|---|---|
| Llama-3.2-3B-Instruct-uncensored | F16 | 5.99 GiB | mradermacher | 6.73 GiB | -10.9% |
| Llama-3.2-3B-Instruct-uncensored | F16 | 5.99 GiB | bartowski | 6.73 GiB | -10.9% |
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 |
|---|---|---|
| Llama-3.2-3B-Instruct-uncensored | 1 | 5.99 GiB |