Is Financial-v1-2B or Llama-3.2-1B-Instruct smaller?

Llama-3.2-1B-Instruct is smaller at Q4_K_M: 0.75 GiB against 1.22 GiB.

Which uses less memory at long context?

Financial-v1-2B — its KV cache at 32K context is 2.7x smaller, because of how its attention layers cache.

Model comparison

Financial-v1-2B vs Llama-3.2-1B-Instruct

At Q4_K_M, Llama-3.2-1B-Instruct is the smaller download — 807,690,688 bytes against 1,312,165,280. At long context the gap widens: Financial-v1-2B's KV cache at 32K is 2.7× smaller, which usually matters more than the difference in weights.

From the file· summed bytes, KV per layer

Side by side

	Financial-v1-2B	Llama-3.2-1B-Instruct
Parameters	1.9B	1.2B
Architecture	qwen35	llama
Layers	24	16
Native context	262,144	131,072
Mixture of experts	no	no
Quantizations published	27	39
Smallest quantization	0.92 GiB	0.39 GiB
Q4_K_M	1.22 GiB	0.75 GiB
Licence	—	—

KV cache by context

the term that decides long-context viability

Context	Financial-v1-2B	Llama-3.2-1B-Instruct	Ratio
4,096	0.05 GiB	0.13 GiB	2.66×
8,192	0.09 GiB	0.25 GiB	2.67×
16,384	0.19 GiB	0.50 GiB	2.67×
32,768	0.38 GiB	1.00 GiB	2.67×
65,536	0.75 GiB	2.00 GiB	2.67×
131,072	1.50 GiB	4.00 GiB	2.67×