Is YuYu1015-Ornith-1.0-9B-abliterated or Qwen3.8-27B smaller?

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

Which uses less memory at long context?

YuYu1015-Ornith-1.0-9B-abliterated — its KV cache at 32K context is 2.0x smaller, because of how its attention layers cache.

Model comparison

YuYu1015-Ornith-1.0-9B-abliterated vs Qwen3.8-27B

These two publish different quantization sets; the table below has the exact sizes. At long context the gap widens: YuYu1015-Ornith-1.0-9B-abliterated'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

	YuYu1015-Ornith-1.0-9B-abliterated	Qwen3.8-27B
Parameters	9.4B	27.8B
Architecture	qwen35	qwen35
Layers	32	64
Native context	262,144	262,144
Mixture of experts	no	no
Quantizations published	3	22
Smallest quantization	5.77 GiB	8.39 GiB
Q4_K_M	—	15.66 GiB
Licence	apache-2.0	apache-2.0

KV cache by context

the term that decides long-context viability

Context	YuYu1015-Ornith-1.0-9B-abliterated	Qwen3.8-27B	Ratio
4,096	0.13 GiB	0.25 GiB	2.00×
8,192	0.25 GiB	0.50 GiB	2.00×
16,384	0.50 GiB	1.00 GiB	2.00×
32,768	1.00 GiB	2.00 GiB	2.00×
65,536	2.00 GiB	4.00 GiB	2.00×
131,072	4.00 GiB	8.00 GiB	2.00×