Is NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 or Qwen3.6-27B smaller?

Qwen3.6-27B is smaller at Q4_K_M: 15.41 GiB against 20.88 GiB.

Which uses less memory at long context?

NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 — its KV cache at 32K context is 1.2x smaller, because of how its attention layers cache.

Model comparison

NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 vs Qwen3.6-27B

At Q4_K_M, Qwen3.6-27B is the smaller download — 16,547,397,888 bytes against 22,421,827,488. At long context the gap widens: NVIDIA-Nemotron-3-Nano-30B-A3B-BF16's KV cache at 32K is 1.2× smaller, which usually matters more than the difference in weights.

From the file· summed bytes, KV per layer

Side by side

	NVIDIA-Nemotron-3-Nano-30B-A3B-BF16	Qwen3.6-27B
Parameters	31.6B	27.8B
Architecture	nemotron_h_moe	qwen35
Layers	52	64
Native context	262,144	262,144
Mixture of experts	yes, 128 experts	no
Quantizations published	25	40
Smallest quantization	16.85 GiB	8.74 GiB
Q4_K_M	20.88 GiB	15.41 GiB
Licence	other	apache-2.0

KV cache by context

the term that decides long-context viability

Context	NVIDIA-Nemotron-3-Nano-30B-A3B-BF16	Qwen3.6-27B	Ratio
4,096	0.20 GiB	0.25 GiB	1.23×
8,192	0.41 GiB	0.50 GiB	1.23×
16,384	0.81 GiB	1.00 GiB	1.23×
32,768	1.63 GiB	2.00 GiB	1.23×
65,536	3.25 GiB	4.00 GiB	1.23×
131,072	6.50 GiB	8.00 GiB	1.23×