Quantization publisher
AdvancedDataIntelligence
AdvancedDataIntelligence publishes 3 quantizations across 3 models in our index, averaging 4.786 effective bits per weight. Their files differ in size from other publishers' builds of the same nominal quantization on 4 of the pairs we can compare — the same label does not mean the same file.
From the file· summed file bytes
Repositories
3
Quantizations
3
Models covered
3
Avg effective bpw
4.786
across their files
Same model, same quant label, different bytes
largest disagreements first
| Model | Quant | AdvancedDataIntelligence | vs | Theirs | Difference |
|---|---|---|---|---|---|
| Qwen2.5-7B-Instruct-abliterated-v2 | Q4_K_M | 4.36 GiB | mradermacher | 4.36 GiB | -0.0% |
| Qwen2.5-7B-Instruct-abliterated-v2 | Q4_K_M | 4.36 GiB | koorbmeh | 4.36 GiB | -0.0% |
| Qwen2.5-Coder-7B | Q4_K_M | 4.36 GiB | itlwas | 4.36 GiB | -0.0% |
| Qwen2.5-VL-7B-Instruct-abliterated | Q4_K_M | 4.36 GiB | mradermacher | 4.36 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-VL-7B-Instruct-abliterated | 1 | 4.36 GiB |
| Qwen2.5-Coder-7B | 1 | 4.36 GiB |
| Qwen2.5-7B-Instruct-abliterated-v2 | 1 | 4.36 GiB |