Quantization publisher

pbatra

pbatra publishes 2 quantizations across 1 models in our index, averaging 6.132 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
1
Quantizations
2
Models covered
1
Avg effective bpw
6.132
across their files

Same model, same quant label, different bytes

largest disagreements first
ModelQuantpbatravsTheirsDifference
Llama-3.2-11B-Vision-InstructQ8_09.68 GiBEnlistedGhost11.43 GiB-15.3%
Llama-3.2-11B-Vision-InstructQ4_K_M5.55 GiBEnlistedGhost7.28 GiB-23.7%
Llama-3.2-11B-Vision-InstructQ4_K_M5.55 GiBleafspark5.55 GiB0.0%
Llama-3.2-11B-Vision-InstructQ8_09.68 GiBleafspark9.68 GiB0.0%

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
Llama-3.2-11B-Vision-Instruct25.55 GiB