Quantization publisher
leafspark
leafspark publishes 3 quantizations across 1 models in our index, averaging 8.976 effective bits per weight. Their files differ in size from other publishers' builds of the same nominal quantization on 5 of the pairs we can compare — the same label does not mean the same file.
From the file· summed file bytes
Repositories
1
Quantizations
3
Models covered
1
Avg effective bpw
8.976
across their files
Same model, same quant label, different bytes
largest disagreements first
| Model | Quant | leafspark | vs | Theirs | Difference |
|---|---|---|---|---|---|
| Llama-3.2-11B-Vision-Instruct | F16 | 18.22 GiB | EnlistedGhost | 20.02 GiB | -9.0% |
| Llama-3.2-11B-Vision-Instruct | Q8_0 | 9.68 GiB | EnlistedGhost | 11.43 GiB | -15.3% |
| Llama-3.2-11B-Vision-Instruct | Q4_K_M | 5.55 GiB | EnlistedGhost | 7.28 GiB | -23.7% |
| Llama-3.2-11B-Vision-Instruct | Q4_K_M | 5.55 GiB | pbatra | 5.55 GiB | -0.0% |
| Llama-3.2-11B-Vision-Instruct | Q8_0 | 9.68 GiB | pbatra | 9.68 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
| Model | Quantizations | Smallest |
|---|---|---|
| Llama-3.2-11B-Vision-Instruct | 3 | 5.55 GiB |