Quantization publisher
DevQuasar-5
DevQuasar-5 publishes 12 quantizations across 2 models in our index, averaging 5.554 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
2
Quantizations
12
Models covered
2
Avg effective bpw
5.554
across their files
Same model, same quant label, different bytes
largest disagreements first
| Model | Quant | DevQuasar-5 | vs | Theirs | Difference |
|---|---|---|---|---|---|
| Qwen2.5-72B-Instruct-abliterated | Q2_K | 27.76 GiB | mradermacher | 27.76 GiB | -0.0% |
| Qwen2.5-72B-Instruct-abliterated | Q3_K_M | 35.11 GiB | mradermacher | 35.11 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 |
|---|---|---|
| Qwen2.5-72B-Instruct-abliterated | 6 | 27.76 GiB |
| Llama-3.3-70B-Instruct-abliterated-finetuned | 6 | 24.56 GiB |