Model comparison

gemma-4-12B-it-qat-q4_0-unquantized vs gemma-3-16b-it-BIG-G-GLM4.7-Flash-Valhalla-Heretic-Uncensored-Deep-Thinking

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

From the file· summed bytes, KV per layer

Side by side

gemma-4-12B-it-qat-q4_0-unquantizedgemma-3-16b-it-BIG-G-GLM4.7-Flash-Valhalla-Heretic-Uncensored-Deep-Thinking
Parameters12.0B16.0B
Architecturegemma4gemma3
Layers48
Native context262,144
Mixture of expertsnono
Quantizations published235
Smallest quantization6.50 GiB3.57 GiB
Q4_K_M9.18 GiB
Licenceapache-2.0apache-2.0

KV cache by context

the term that decides long-context viability
Contextgemma-4-12B-it-qat-q4_0-unquantizedgemma-3-16b-it-BIG-G-GLM4.7-Flash-Valhalla-Heretic-Uncensored-Deep-ThinkingRatio
4,0960.72 GiB
8,1920.97 GiB
16,3841.47 GiB
32,7682.47 GiB
65,5364.47 GiB
131,0728.47 GiB
gemma-4-12B-it-qat-q4_0-unquantized vs gemma-3-16b-it-BIG-G-GLM4.7-Flash-Valhalla-Heretic-Uncensored-Deep-Thinking — size, memory and hardware fit — ossmodeldb