Is LFM2-24B-A2B 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?

LFM2-24B-A2B — its KV cache at 32K context is 3.9x smaller, because of how its attention layers cache.

Model comparison

LFM2-24B-A2B 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: LFM2-24B-A2B's KV cache at 32K is 3.9× smaller, which usually matters more than the difference in weights.

From the file· summed bytes, KV per layer

Side by side

	LFM2-24B-A2B	gemma-4-12B-it-qat-q4_0-unquantized
Parameters	23.8B	12.0B
Architecture	lfm2moe	gemma4
Layers	40	48
Native context	128,000	262,144
Mixture of experts	yes, 64 experts	no
Quantizations published	33	2
Smallest quantization	5.35 GiB	6.50 GiB
Q4_K_M	13.43 GiB	—
Licence	other	apache-2.0

KV cache by context

the term that decides long-context viability

Context	LFM2-24B-A2B	gemma-4-12B-it-qat-q4_0-unquantized	Ratio
4,096	0.08 GiB	0.72 GiB	9.19×
8,192	0.16 GiB	0.97 GiB	6.20×
16,384	0.31 GiB	1.47 GiB	4.70×
32,768	0.63 GiB	2.47 GiB	3.95×
65,536	1.25 GiB	4.47 GiB	3.57×
131,072	2.50 GiB	8.47 GiB	3.39×