Quantization publisher

ekampra

ekampra publishes 11 quantizations across 1 models in our index, averaging 9.153 effective bits per weight. Their files differ in size from other publishers' builds of the same nominal quantization on 7 of the pairs we can compare — the same label does not mean the same file.

From the file· summed file bytes
Repositories
1
Quantizations
11
Models covered
1
Avg effective bpw
9.153
across their files

Same model, same quant label, different bytes

largest disagreements first
ModelQuantekampravsTheirsDifference
Mistral-MOE-4X7B-Dark-MultiVerse-Uncensored-Enhanced32-24BQ5_K_S15.53 GiBDevQuasar-915.48 GiB+0.3%
Mistral-MOE-4X7B-Dark-MultiVerse-Uncensored-Enhanced32-24BQ5_K_M16.00 GiBDevQuasar-915.96 GiB+0.3%
Mistral-MOE-4X7B-Dark-MultiVerse-Uncensored-Enhanced32-24BQ3_K_L11.73 GiBDevQuasar-911.68 GiB+0.4%
Mistral-MOE-4X7B-Dark-MultiVerse-Uncensored-Enhanced32-24BQ3_K_M10.83 GiBDevQuasar-910.79 GiB+0.4%
Mistral-MOE-4X7B-Dark-MultiVerse-Uncensored-Enhanced32-24BQ3_K_S9.76 GiBDevQuasar-99.72 GiB+0.5%
Mistral-MOE-4X7B-Dark-MultiVerse-Uncensored-Enhanced32-24BQ4_K_M13.65 GiBDevQuasar-913.61 GiB+0.3%
Mistral-MOE-4X7B-Dark-MultiVerse-Uncensored-Enhanced32-24BQ4_K_S12.84 GiBDevQuasar-912.80 GiB+0.4%

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