Is functiongemma-270m-it or Llama-3.2-1B-Instruct smaller?

functiongemma-270m-it is smaller at Q4_K_M: 0.24 GiB against 0.75 GiB.

Which uses less memory at long context?

functiongemma-270m-it — its KV cache at 32K context is 9.2x smaller, because of how its attention layers cache.

Model comparison

functiongemma-270m-it vs Llama-3.2-1B-Instruct

At Q4_K_M, functiongemma-270m-it is the smaller download — 253,127,392 bytes against 807,690,688. At long context the gap widens: functiongemma-270m-it's KV cache at 32K is 9.2× smaller, which usually matters more than the difference in weights.

From the file· summed bytes, KV per layer

Side by side

	functiongemma-270m-it	Llama-3.2-1B-Instruct
Parameters	268M	1.2B
Architecture	gemma3	llama
Layers	18	16
Native context	32,768	131,072
Mixture of experts	no	no
Quantizations published	45	39
Smallest quantization	0.17 GiB	0.39 GiB
Q4_K_M	0.24 GiB	0.75 GiB
Licence	gemma	—

KV cache by context

the term that decides long-context viability

Context	functiongemma-270m-it	Llama-3.2-1B-Instruct	Ratio
4,096	0.03 GiB	0.13 GiB	4.74×
8,192	0.04 GiB	0.25 GiB	6.56×
16,384	0.06 GiB	0.50 GiB	8.13×
32,768	0.11 GiB	1.00 GiB	9.23×
65,536	0.20 GiB	2.00 GiB	9.89×
131,072	0.39 GiB	4.00 GiB	10.27×