Is Qwen3-4B-Qwen3.6-plus-Reasoning-Distilled or llama-3-youko-8b smaller?

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

Which uses less memory at long context?

llama-3-youko-8b — its KV cache at 32K context is 1.1x smaller, because of how its attention layers cache.

Model comparison

These two publish different quantization sets; the table below has the exact sizes.

From the file· summed bytes, KV per layer

	Qwen3-4B-Qwen3.6-plus-Reasoning-Distilled	llama-3-youko-8b
Parameters	4.0B	8.0B
Architecture	qwen3	llama
Layers	36	32
Native context	262,144	8,192
Mixture of experts	no	no
Quantizations published	3	2
Smallest quantization	2.42 GiB	5.34 GiB
Q4_K_M	—	—
Licence	apache-2.0	llama3

the term that decides long-context viability

Context	Qwen3-4B-Qwen3.6-plus-Reasoning-Distilled	llama-3-youko-8b	Ratio
4,096	0.56 GiB	0.50 GiB	1.13×
8,192	1.13 GiB	1.00 GiB	1.13×
16,384	2.25 GiB	2.00 GiB	1.13×
32,768	4.50 GiB	4.00 GiB	1.13×
65,536	9.00 GiB	8.00 GiB	1.13×
131,072	18.00 GiB	16.00 GiB	1.13×