Is MythoMax-L2-Kimiko-v2-13b or Qwen3-30B-A3B-Thinking-2507 smaller?

MythoMax-L2-Kimiko-v2-13b is smaller at Q4_K_M: 7.33 GiB against 17.28 GiB.

Which uses less memory at long context?

Qwen3-30B-A3B-Thinking-2507 — its KV cache at 32K context is 8.3x smaller, because of how its attention layers cache.

Model comparison

MythoMax-L2-Kimiko-v2-13b vs Qwen3-30B-A3B-Thinking-2507

At Q4_K_M, MythoMax-L2-Kimiko-v2-13b is the smaller download — 7,865,956,224 bytes against 18,556,685,824. At long context the gap widens: Qwen3-30B-A3B-Thinking-2507's KV cache at 32K is 8.3× smaller, which usually matters more than the difference in weights.

From the file· summed bytes, KV per layer

Side by side

	MythoMax-L2-Kimiko-v2-13b	Qwen3-30B-A3B-Thinking-2507
Parameters	13.0B	30.5B
Architecture	llama	qwen3moe
Layers	40	48
Native context	4,096	262,144
Mixture of experts	no	yes, 128 experts
Quantizations published	26	51
Smallest quantization	4.70 GiB	7.05 GiB
Q4_K_M	7.33 GiB	17.28 GiB
Licence	cc-by-nc-4.0	apache-2.0

KV cache by context

the term that decides long-context viability

Context	MythoMax-L2-Kimiko-v2-13b	Qwen3-30B-A3B-Thinking-2507	Ratio
4,096	3.13 GiB	0.38 GiB	8.33×
8,192	6.25 GiB	0.75 GiB	8.33×
16,384	12.50 GiB	1.50 GiB	8.33×
32,768	25.00 GiB	3.00 GiB	8.33×
65,536	50.00 GiB	6.00 GiB	8.33×
131,072	100.00 GiB	12.00 GiB	8.33×