Is magnum-v2-12b or gemma-4-12B-it-qat-q4_0-unquantized smaller?

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

Which uses less memory at long context?

gemma-4-12B-it-qat-q4_0-unquantized — its KV cache at 32K context is 2.0x smaller, because of how its attention layers cache.

Model comparison

magnum-v2-12b vs gemma-4-12B-it-qat-q4_0-unquantized

These two publish different quantization sets; the table below has the exact sizes. At long context the gap widens: gemma-4-12B-it-qat-q4_0-unquantized's KV cache at 32K is 2.0× smaller, which usually matters more than the difference in weights.

From the file· summed bytes, KV per layer

Side by side

	magnum-v2-12b	gemma-4-12B-it-qat-q4_0-unquantized
Parameters	12.2B	12.0B
Architecture	llama	gemma4
Layers	40	48
Native context	1,024,000	262,144
Mixture of experts	no	no
Quantizations published	45	2
Smallest quantization	2.79 GiB	6.50 GiB
Q4_K_M	6.96 GiB	—
Licence	apache-2.0	apache-2.0

KV cache by context

the term that decides long-context viability

Context	magnum-v2-12b	gemma-4-12B-it-qat-q4_0-unquantized	Ratio
4,096	0.63 GiB	0.72 GiB	1.15×
8,192	1.25 GiB	0.97 GiB	1.29×
16,384	2.50 GiB	1.47 GiB	1.70×
32,768	5.00 GiB	2.47 GiB	2.03×
65,536	10.00 GiB	4.47 GiB	2.24×
131,072	20.00 GiB	8.47 GiB	2.36×