Is oxy-1-small 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 1.5x smaller, because of how its attention layers cache.

Model comparison

oxy-1-small vs llama-3-youko-8b

These two publish different quantization sets; the table below has the exact sizes. At long context the gap widens: llama-3-youko-8b's KV cache at 32K is 1.5× smaller, which usually matters more than the difference in weights.

From the file· summed bytes, KV per layer

Side by side

	oxy-1-small	llama-3-youko-8b
Parameters	14.8B	8.0B
Architecture	qwen2	llama
Layers	48	32
Native context	32,768	8,192
Mixture of experts	no	no
Quantizations published	22	2
Smallest quantization	4.66 GiB	5.34 GiB
Q4_K_M	8.37 GiB	—
Licence	apache-2.0	llama3

KV cache by context

the term that decides long-context viability

Context	oxy-1-small	llama-3-youko-8b	Ratio
4,096	0.75 GiB	0.50 GiB	1.50×
8,192	1.50 GiB	1.00 GiB	1.50×
16,384	3.00 GiB	2.00 GiB	1.50×
32,768	6.00 GiB	4.00 GiB	1.50×
65,536	12.00 GiB	8.00 GiB	1.50×
131,072	24.00 GiB	16.00 GiB	1.50×