Is Open_Gpt4_8x7B_v0.1 or Qwen3.6-27B smaller?

Qwen3.6-27B is smaller at Q4_K_M: 15.41 GiB against 24.63 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

Open_Gpt4_8x7B_v0.1 vs Qwen3.6-27B

At Q4_K_M, Qwen3.6-27B is the smaller download — 16,547,397,888 bytes against 26,442,469,184. 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

	Open_Gpt4_8x7B_v0.1	Qwen3.6-27B
Parameters	46.7B	27.8B
Architecture	llama	qwen35
Layers	32	64
Native context	32,768	262,144
Mixture of experts	yes, 8 experts	no
Quantizations published	8	40
Smallest quantization	14.57 GiB	8.74 GiB
Q4_K_M	24.63 GiB	15.41 GiB
Licence	apache-2.0	apache-2.0

KV cache by context

the term that decides long-context viability

Context	Open_Gpt4_8x7B_v0.1	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×