Is llama-3-youko-8b or Qwen3.6-27B smaller?

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

Which uses less memory at long context?

Qwen3.6-27B — its KV cache at 32K context is 2.0x smaller, because of how its attention layers cache.

Model comparison

llama-3-youko-8b vs Qwen3.6-27B

These two publish different quantization sets; the table below has the exact sizes. At long context the gap widens: Qwen3.6-27B's KV cache at 32K is 2.0× smaller, which usually matters more than the difference in weights.

From the file· summed bytes, KV per layer

Side by side

	llama-3-youko-8b	Qwen3.6-27B
Parameters	8.0B	27.8B
Architecture	llama	qwen35
Layers	32	64
Native context	8,192	262,144
Mixture of experts	no	no
Quantizations published	2	40
Smallest quantization	5.34 GiB	8.74 GiB
Q4_K_M	—	15.41 GiB
Licence	llama3	apache-2.0

KV cache by context

the term that decides long-context viability

Context	llama-3-youko-8b	Qwen3.6-27B	Ratio
4,096	0.50 GiB	0.25 GiB	2.00×
8,192	1.00 GiB	0.50 GiB	2.00×
16,384	2.00 GiB	1.00 GiB	2.00×
32,768	4.00 GiB	2.00 GiB	2.00×
65,536	8.00 GiB	4.00 GiB	2.00×
131,072	16.00 GiB	8.00 GiB	2.00×