Is OneLLM-Doey-V1-Llama-3.2-1B-it or Qwen3-4B smaller?

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

Which uses less memory at long context?

OneLLM-Doey-V1-Llama-3.2-1B-it — its KV cache at 32K context is 4.5x smaller, because of how its attention layers cache.

Model comparison

OneLLM-Doey-V1-Llama-3.2-1B-it vs Qwen3-4B

These two publish different quantization sets; the table below has the exact sizes. At long context the gap widens: OneLLM-Doey-V1-Llama-3.2-1B-it's KV cache at 32K is 4.5× smaller, which usually matters more than the difference in weights.

From the file· summed bytes, KV per layer

Side by side

	OneLLM-Doey-V1-Llama-3.2-1B-it	Qwen3-4B
Parameters	1.2B	4.0B
Architecture	llama	qwen3
Layers	16	36
Native context	131,072	40,960
Mixture of experts	no	no
Quantizations published	1	29
Smallest quantization	1.23 GiB	1.01 GiB
Q4_K_M	—	2.33 GiB
Licence	apache-2.0	—

KV cache by context

the term that decides long-context viability

Context	OneLLM-Doey-V1-Llama-3.2-1B-it	Qwen3-4B	Ratio
4,096	0.13 GiB	0.56 GiB	4.50×
8,192	0.25 GiB	1.13 GiB	4.50×
16,384	0.50 GiB	2.25 GiB	4.50×
32,768	1.00 GiB	4.50 GiB	4.50×
65,536	2.00 GiB	9.00 GiB	4.50×
131,072	4.00 GiB	18.00 GiB	4.50×