Is Qwen3-15B-A2B-Base or Qwen3-30B-A3B-Thinking-2507 smaller?

Qwen3-15B-A2B-Base is smaller at Q4_K_M: 8.84 GiB against 17.28 GiB.

Which uses less memory at long context?

Qwen3-15B-A2B-Base — its KV cache at 32K context is 2.0x smaller, because of how its attention layers cache.

Model comparison

Qwen3-15B-A2B-Base vs Qwen3-30B-A3B-Thinking-2507

At Q4_K_M, Qwen3-15B-A2B-Base is the smaller download — 9,496,453,792 bytes against 18,556,685,824. At long context the gap widens: Qwen3-15B-A2B-Base's KV cache at 32K is 2.0× smaller, which usually matters more than the difference in weights.

From the file· summed bytes, KV per layer

Side by side

	Qwen3-15B-A2B-Base	Qwen3-30B-A3B-Thinking-2507
Parameters	15.6B	30.5B
Architecture	qwen3moe	qwen3moe
Layers	24	48
Native context	4,096	262,144
Mixture of experts	yes, 128 experts	yes, 128 experts
Quantizations published	11	51
Smallest quantization	5.41 GiB	7.05 GiB
Q4_K_M	8.84 GiB	17.28 GiB
Licence	apache-2.0	apache-2.0

KV cache by context

the term that decides long-context viability

Context	Qwen3-15B-A2B-Base	Qwen3-30B-A3B-Thinking-2507	Ratio
4,096	0.19 GiB	0.38 GiB	2.00×
8,192	0.38 GiB	0.75 GiB	2.00×
16,384	0.75 GiB	1.50 GiB	2.00×
32,768	1.50 GiB	3.00 GiB	2.00×
65,536	3.00 GiB	6.00 GiB	2.00×
131,072	6.00 GiB	12.00 GiB	2.00×