Quantization publisher

Abhijith93

Abhijith93 publishes 2 quantizations across 1 models in our index, averaging 6.281 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
1
Quantizations
2
Models covered
1
Avg effective bpw
6.281
across their files

Same model, same quant label, different bytes

largest disagreements first
ModelQuantAbhijith93vsTheirsDifference
Qwen3.5-9B-Claude-4.6-Opus-Reasoning-Distilled-v2Q4_K_M5.24 GiBAbiray5.24 GiB-0.0%
Qwen3.5-9B-Claude-4.6-Opus-Reasoning-Distilled-v2Q8_08.87 GiBAbiray8.87 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
Qwen3.5-9B-Claude-4.6-Opus-Reasoning-Distilled-v225.24 GiB