Is Yi-34B-200K-Llamafied or Qwen3.6-27B smaller?

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

Which uses less memory at long context?

Qwen3.6-27B — its KV cache at 32K context is 3.7x smaller, because of how its attention layers cache.

Model comparison

Yi-34B-200K-Llamafied vs Qwen3.6-27B

These two publish different quantization sets; the table below has the exact sizes. At long context the gap widens: Qwen3.6-27B's KV cache at 32K is 3.7× smaller, which usually matters more than the difference in weights.

From the file· summed bytes, KV per layer

Side by side

	Yi-34B-200K-Llamafied	Qwen3.6-27B
Parameters	34.4B	27.8B
Architecture	llama	qwen35
Layers	60	64
Native context	200,000	262,144
Mixture of experts	no	no
Quantizations published	21	40
Smallest quantization	6.98 GiB	8.74 GiB
Q4_K_M	—	15.41 GiB
Licence	apache-2.0	apache-2.0

KV cache by context

the term that decides long-context viability

Context	Yi-34B-200K-Llamafied	Qwen3.6-27B	Ratio
4,096	0.94 GiB	0.25 GiB	3.75×
8,192	1.88 GiB	0.50 GiB	3.75×
16,384	3.75 GiB	1.00 GiB	3.75×
32,768	7.50 GiB	2.00 GiB	3.75×
65,536	15.00 GiB	4.00 GiB	3.75×
131,072	30.00 GiB	8.00 GiB	3.75×