Model comparison

gemma4-E4B-it-abliterated vs Qwen3-8B

These two publish different quantization sets; the table below has the exact sizes. At long context the gap widens: gemma4-E4B-it-abliterated's KV cache at 32K is 8.9× smaller, which usually matters more than the difference in weights.

From the file· summed bytes, KV per layer

Side by side

gemma4-E4B-it-abliteratedQwen3-8B
Parameters7.9B8.2B
Architecturegemma4qwen3
Layers4236
Native context131,07240,960
Mixture of expertsnono
Quantizations published2451
Smallest quantization3.06 GiB2.12 GiB
Q4_K_M4.68 GiB
Licenceapache-2.0apache-2.0

KV cache by context

the term that decides long-context viability
Contextgemma4-E4B-it-abliteratedQwen3-8BRatio
4,0960.12 GiB0.56 GiB4.57×
8,1920.18 GiB1.13 GiB6.33×
16,3840.29 GiB2.25 GiB7.84×
32,7680.51 GiB4.50 GiB8.90×
65,5360.94 GiB9.00 GiB9.54×
131,0721.82 GiB18.00 GiB9.90×
gemma4-E4B-it-abliterated vs Qwen3-8B — size, memory and hardware fit — ossmodeldb