Is Qwen3.8-27B or openbuddy-deepseek-67b-v15.3-4k smaller?

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

Which uses less memory at long context?

Qwen3.8-27B — its KV cache at 32K context is 5.9x smaller, because of how its attention layers cache.

Model comparison

Qwen3.8-27B vs openbuddy-deepseek-67b-v15.3-4k

These two publish different quantization sets; the table below has the exact sizes. At long context the gap widens: Qwen3.8-27B's KV cache at 32K is 5.9× smaller, which usually matters more than the difference in weights.

From the file· summed bytes, KV per layer

Side by side

	Qwen3.8-27B	openbuddy-deepseek-67b-v15.3-4k
Parameters	27.8B	67.4B
Architecture	qwen35	llama
Layers	64	95
Native context	262,144	4,096
Mixture of experts	no	no
Quantizations published	22	20
Smallest quantization	8.39 GiB	13.65 GiB
Q4_K_M	15.66 GiB	—
Licence	apache-2.0	other

KV cache by context

the term that decides long-context viability

Context	Qwen3.8-27B	openbuddy-deepseek-67b-v15.3-4k	Ratio
4,096	0.25 GiB	1.48 GiB	5.93×
8,192	0.50 GiB	2.97 GiB	5.94×
16,384	1.00 GiB	5.94 GiB	5.94×
32,768	2.00 GiB	11.88 GiB	5.94×
65,536	4.00 GiB	23.75 GiB	5.94×
131,072	8.00 GiB	47.50 GiB	5.94×