Model comparison

NVIDIA-Nemotron-Nano-12B-v2 vs gemma-4-E4B-it

At Q4_K_M, gemma-4-E4B-it is the smaller download — 4,977,171,584 bytes against 7,494,497,504. At long context the gap widens: gemma-4-E4B-it's KV cache at 32K is 15.3× smaller, which usually matters more than the difference in weights.

From the file· summed bytes, KV per layer

Side by side

NVIDIA-Nemotron-Nano-12B-v2gemma-4-E4B-it
Parameters12.3B8.0B
Architecturenemotron_hgemma4
Layers6242
Native context131,072131,072
Mixture of expertsnono
Quantizations published3036
Smallest quantization3.79 GiB3.30 GiB
Q4_K_M6.98 GiB4.64 GiB
Licenceapache-2.0

KV cache by context

the term that decides long-context viability
ContextNVIDIA-Nemotron-Nano-12B-v2gemma-4-E4B-itRatio
4,0960.97 GiB0.12 GiB7.87×
8,1921.94 GiB0.18 GiB10.90×
16,3843.88 GiB0.29 GiB13.50×
32,7687.75 GiB0.51 GiB15.32×
65,53615.50 GiB0.94 GiB16.43×
131,07231.00 GiB1.82 GiB17.05×
NVIDIA-Nemotron-Nano-12B-v2 vs gemma-4-E4B-it — size, memory and hardware fit — ossmodeldb