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 Mistral-MOE-4X7B-Dark-MultiVerse-Uncensored-Enhanced32-24B

Q: Is Qwen3.6-27B or Mistral-MOE-4X7B-Dark-MultiVerse-Uncensored-Enhanced32-24B smaller?

Mistral-MOE-4X7B-Dark-MultiVerse-Uncensored-Enhanced32-24B is smaller at Q4_K_M: 13.61 GiB against 15.41 GiB.

At Q4_K_M, Mistral-MOE-4X7B-Dark-MultiVerse-Uncensored-Enhanced32-24B is the smaller download — 14,609,885,184 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	Mistral-MOE-4X7B-Dark-MultiVerse-Uncensored-Enhanced32-24B
Parameters	27.8B	24.2B
Architecture	qwen35	llama
Layers	64	32
Native context	262,144	32,768
Mixture of experts	no	yes, 4 experts
Quantizations published	40	33
Smallest quantization	8.74 GiB	8.24 GiB
Q4_K_M	15.41 GiB	13.61 GiB
Licence	apache-2.0	apache-2.0

KV cache by context

the term that decides long-context viability

Context	Qwen3.6-27B	Mistral-MOE-4X7B-Dark-MultiVerse-Uncensored-Enhanced32-24B	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×