Is gemma-4-12B-it-qat-q4_0-unquantized or gpt-oss-20b smaller?

Both publish quantizations; compare the table for the exact sizes.

Which uses less memory at long context?

gpt-oss-20b — its KV cache at 32K context is 3.2x smaller, because of how its attention layers cache.

Model comparison

gemma-4-12B-it-qat-q4_0-unquantized vs gpt-oss-20b

These two publish different quantization sets; the table below has the exact sizes. At long context the gap widens: gpt-oss-20b's KV cache at 32K is 3.2× smaller, which usually matters more than the difference in weights.

From the file· summed bytes, KV per layer

Side by side

	gemma-4-12B-it-qat-q4_0-unquantized	gpt-oss-20b
Parameters	12.0B	21.5B
Architecture	gemma4	gpt-oss
Layers	48	24
Native context	262,144	131,072
Mixture of experts	no	yes, 32 experts
Quantizations published	2	15
Smallest quantization	6.50 GiB	10.68 GiB
Q4_K_M	—	10.83 GiB
Licence	apache-2.0	apache-2.0

KV cache by context

the term that decides long-context viability

Context	gemma-4-12B-it-qat-q4_0-unquantized	gpt-oss-20b	Ratio
4,096	0.72 GiB	0.11 GiB	6.46×
8,192	0.97 GiB	0.21 GiB	4.72×
16,384	1.47 GiB	0.39 GiB	3.74×
32,768	2.47 GiB	0.77 GiB	3.22×
65,536	4.47 GiB	1.52 GiB	2.94×
131,072	8.47 GiB	3.02 GiB	2.81×