Is Qwen3.6-27B or deepseek-r1-distill-llama-8b-unsloth-bnb-4bit smaller?

deepseek-r1-distill-llama-8b-unsloth-bnb-4bit is smaller at Q4_K_M: 14.97 GiB against 15.41 GiB.

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

Qwen3.6-27B vs deepseek-r1-distill-llama-8b-unsloth-bnb-4bit

At Q4_K_M, deepseek-r1-distill-llama-8b-unsloth-bnb-4bit is the smaller download — 16,068,894,016 bytes against 16,547,397,888. 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

	Qwen3.6-27B	deepseek-r1-distill-llama-8b-unsloth-bnb-4bit
Parameters	27.8B	8.2B
Architecture	qwen35	llama
Layers	64	32
Native context	262,144	131,072
Mixture of experts	no	no
Quantizations published	40	2
Smallest quantization	8.74 GiB	7.95 GiB
Q4_K_M	15.41 GiB	14.97 GiB
Licence	apache-2.0	apache-2.0

KV cache by context

the term that decides long-context viability

Context	Qwen3.6-27B	deepseek-r1-distill-llama-8b-unsloth-bnb-4bit	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×