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

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

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

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

KV cache by context

the term that decides long-context viability

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