Quantization publisher

koorbmeh

koorbmeh publishes 1 quantizations across 1 models in our index, averaging 4.919 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
4.919
across their files

Same model, same quant label, different bytes

largest disagreements first
ModelQuantkoorbmehvsTheirsDifference
Qwen2.5-7B-Instruct-abliterated-v2Q4_K_M4.36 GiBAdvancedDataIntelligence4.36 GiB0.0%
Qwen2.5-7B-Instruct-abliterated-v2Q4_K_M4.36 GiBmradermacher4.36 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

ModelQuantizationsSmallest
Qwen2.5-7B-Instruct-abliterated-v214.36 GiB