Quantization publisher

sahilchachra

sahilchachra publishes 13 quantizations across 1 models in our index, averaging 5.276 effective bits per weight. Their files differ in size from other publishers' builds of the same nominal quantization on 8 of the pairs we can compare — the same label does not mean the same file.

From the file· summed file bytes
Repositories
1
Quantizations
13
Models covered
1
Avg effective bpw
5.276
across their files

Same model, same quant label, different bytes

largest disagreements first
ModelQuantsahilchachravsTheirsDifference
Unlimited-OCRQ6_K2.43 GiBDevQuasar2.43 GiB0.0%
Unlimited-OCRQ8_02.91 GiBDevQuasar2.91 GiB0.0%
Unlimited-OCRQ4_K_M1.82 GiBDevQuasar1.82 GiB0.0%
Unlimited-OCRQ3_K_M1.45 GiBDevQuasar1.45 GiB0.0%
Unlimited-OCRQ5_K_M2.07 GiBDevQuasar2.07 GiB0.0%
Unlimited-OCRQ8_02.91 GiBsabafallah2.91 GiB0.0%
Unlimited-OCRQ4_K_M1.82 GiBsabafallah1.82 GiB0.0%
Unlimited-OCRBF165.47 GiBsabafallah5.47 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
Unlimited-OCR131.15 GiB