Is Qwen3.8-27B or Meta-Llama-3-70B-Instruct-abliterated-v3.5 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 5.0x smaller, because of how its attention layers cache.

Model comparison

Qwen3.8-27B vs Meta-Llama-3-70B-Instruct-abliterated-v3.5

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 5.0× smaller, which usually matters more than the difference in weights.

From the file· summed bytes, KV per layer

Side by side

	Qwen3.8-27B	Meta-Llama-3-70B-Instruct-abliterated-v3.5
Parameters	27.8B	70.6B
Architecture	qwen35	llama
Layers	64	80
Native context	262,144	8,192
Mixture of experts	no	no
Quantizations published	22	44
Smallest quantization	8.39 GiB	14.29 GiB
Q4_K_M	15.66 GiB	—
Licence	apache-2.0	llama3

KV cache by context

the term that decides long-context viability

Context	Qwen3.8-27B	Meta-Llama-3-70B-Instruct-abliterated-v3.5	Ratio
4,096	0.25 GiB	1.25 GiB	5.00×
8,192	0.50 GiB	2.50 GiB	5.00×
16,384	1.00 GiB	5.00 GiB	5.00×
32,768	2.00 GiB	10.00 GiB	5.00×
65,536	4.00 GiB	20.00 GiB	5.00×
131,072	8.00 GiB	40.00 GiB	5.00×