Model comparison

L3-V2-Stheno-Maid-Blackroot-Grand-HORROR-17B-GLM4.7-Thinking-UNCENSORED vs gemma-4-12B-it-qat-q4_0-unquantized

These two publish different quantization sets; the table below has the exact sizes.

From the file· summed bytes, KV per layer

Side by side

L3-V2-Stheno-Maid-Blackroot-Grand-HORROR-17B-GLM4.7-Thinking-UNCENSOREDgemma-4-12B-it-qat-q4_0-unquantized
Parameters16.5B12.0B
Architecturellamagemma4
Layers48
Native context262,144
Mixture of expertsnono
Quantizations published342
Smallest quantization3.55 GiB6.50 GiB
Q4_K_M9.45 GiB
Licenceapache-2.0apache-2.0

KV cache by context

the term that decides long-context viability
ContextL3-V2-Stheno-Maid-Blackroot-Grand-HORROR-17B-GLM4.7-Thinking-UNCENSOREDgemma-4-12B-it-qat-q4_0-unquantizedRatio
4,0960.72 GiB
8,1920.97 GiB
16,3841.47 GiB
32,7682.47 GiB
65,5364.47 GiB
131,0728.47 GiB
L3-V2-Stheno-Maid-Blackroot-Grand-HORROR-17B-GLM4.7-Thinking-UNCENSORED vs gemma-4-12B-it-qat-q4_0-unquantized — size, memory and hardware fit — ossmodeldb