Is NVIDIA-Nemotron-Nano-9B-v2 or Qwen3-Coder-30B-A3B-Instruct smaller?

NVIDIA-Nemotron-Nano-9B-v2 is smaller at Q4_K_M: 6.08 GiB against 17.28 GiB.

Which uses less memory at long context?

Qwen3-Coder-30B-A3B-Instruct — its KV cache at 32K context is 2.3x smaller, because of how its attention layers cache.

Model comparison

NVIDIA-Nemotron-Nano-9B-v2 vs Qwen3-Coder-30B-A3B-Instruct

At Q4_K_M, NVIDIA-Nemotron-Nano-9B-v2 is the smaller download — 6,525,628,992 bytes against 18,556,689,568. At long context the gap widens: Qwen3-Coder-30B-A3B-Instruct's KV cache at 32K is 2.3× smaller, which usually matters more than the difference in weights.

From the file· summed bytes, KV per layer

Side by side

	NVIDIA-Nemotron-Nano-9B-v2	Qwen3-Coder-30B-A3B-Instruct
Parameters	8.9B	30.5B
Architecture	nemotron_h	qwen3moe
Layers	56	48
Native context	131,072	262,144
Mixture of experts	no	yes, 128 experts
Quantizations published	34	46
Smallest quantization	4.62 GiB	7.46 GiB
Q4_K_M	6.08 GiB	17.28 GiB
Licence	—	apache-2.0

KV cache by context

the term that decides long-context viability

Context	NVIDIA-Nemotron-Nano-9B-v2	Qwen3-Coder-30B-A3B-Instruct	Ratio
4,096	0.88 GiB	0.38 GiB	2.33×
8,192	1.75 GiB	0.75 GiB	2.33×
16,384	3.50 GiB	1.50 GiB	2.33×
32,768	7.00 GiB	3.00 GiB	2.33×
65,536	14.00 GiB	6.00 GiB	2.33×
131,072	28.00 GiB	12.00 GiB	2.33×