Quantization publisher

dahara1

dahara1 publishes 28 quantizations across 2 models in our index, averaging 4.933 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
2
Quantizations
28
Models covered
2
Avg effective bpw
4.933
across their files

Same model, same quant label, different bytes

largest disagreements first
ModelQuantdahara1vsTheirsDifference
gemma-4-E4B-itQ4_K_M4.64 GiBtrjxter4.97 GiB-6.7%
gemma-4-E4B-itQ4_K_M4.64 GiBpankajpandey-dev4.97 GiB-6.7%
gemma-4-E4B-itQ5_K_M5.11 GiBtrjxter5.37 GiB-4.9%
gemma-4-E4B-itQ5_K_M5.11 GiBpankajpandey-dev5.37 GiB-4.9%
gemma-4-E4B-itQ6_K5.95 GiBtrjxter5.79 GiB+2.8%
gemma-4-E4B-itQ8_07.63 GiBpankajpandey-dev7.48 GiB+2.0%
gemma-4-E4B-itQ8_07.63 GiBtrjxter7.48 GiB+2.0%
gemma-4-E2B-itQ8_04.70 GiBAlienstro4.63 GiB+1.6%

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
gemma-4-E4B-it143.29 GiB
gemma-4-E2B-it142.13 GiB