Is Qwen3.8-27B or DeepSeek-R1-Distill-Llama-8B-Abliterated smaller?

DeepSeek-R1-Distill-Llama-8B-Abliterated is smaller at Q4_K_M: 9.17 GiB against 15.66 GiB.

Which uses less memory at long context?

Qwen3.8-27B — its KV cache at 32K context is 2.0x smaller, because of how its attention layers cache.

Model comparison

Qwen3.8-27B vs DeepSeek-R1-Distill-Llama-8B-Abliterated

At Q4_K_M, DeepSeek-R1-Distill-Llama-8B-Abliterated is the smaller download — 9,841,474,624 bytes against 16,810,714,336. At long context the gap widens: Qwen3.8-27B'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

	Qwen3.8-27B	DeepSeek-R1-Distill-Llama-8B-Abliterated
Parameters	27.8B	8.0B
Architecture	qwen35	llama
Layers	64	32
Native context	262,144	131,072
Mixture of experts	no	no
Quantizations published	22	60
Smallest quantization	8.39 GiB	3.76 GiB
Q4_K_M	15.66 GiB	9.17 GiB
Licence	apache-2.0	—

KV cache by context

the term that decides long-context viability

Context	Qwen3.8-27B	DeepSeek-R1-Distill-Llama-8B-Abliterated	Ratio
4,096	0.25 GiB	0.50 GiB	2.00×
8,192	0.50 GiB	1.00 GiB	2.00×
16,384	1.00 GiB	2.00 GiB	2.00×
32,768	2.00 GiB	4.00 GiB	2.00×
65,536	4.00 GiB	8.00 GiB	2.00×
131,072	8.00 GiB	16.00 GiB	2.00×