Quantization publisher

Lamapi

Lamapi publishes 2 quantizations across 2 models in our index, averaging 4.749 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
2
Models covered
2
Avg effective bpw
4.749
across their files

Same model, same quant label, different bytes

largest disagreements first
ModelQuantLamapivsTheirsDifference
next-ocrQ4_K_M4.68 GiBthelamapi4.68 GiB-0.0%
next-8bQ4_K_M4.68 GiBmradermacher4.68 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
next-8b14.68 GiB
next-ocr14.68 GiB