Model comparison

Llama-3.2-8X3B-GATED-MOE-Reasoning-Dark-Champion-Instruct-uncensored-abliterated-18.4B 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

Llama-3.2-8X3B-GATED-MOE-Reasoning-Dark-Champion-Instruct-uncensored-abliterated-18.4Bgemma-4-12B-it-qat-q4_0-unquantized
Parameters18.4B12.0B
Architecturellamagemma4
Layers48
Native context262,144
Mixture of expertsnono
Quantizations published112
Smallest quantization6.65 GiB6.50 GiB
Q4_K_M10.62 GiB
Licenceapache-2.0apache-2.0

KV cache by context

the term that decides long-context viability
ContextLlama-3.2-8X3B-GATED-MOE-Reasoning-Dark-Champion-Instruct-uncensored-abliterated-18.4Bgemma-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