Is Dolphin3.0-R1-Mistral-24B or Qwen3-30B-A3B-Thinking-2507 smaller?

Dolphin3.0-R1-Mistral-24B is smaller at Q4_K_M: 12.17 GiB against 17.28 GiB.

Which uses less memory at long context?

Qwen3-30B-A3B-Thinking-2507 — its KV cache at 32K context is 1.7x smaller, because of how its attention layers cache.

Model comparison

Dolphin3.0-R1-Mistral-24B vs Qwen3-30B-A3B-Thinking-2507

At Q4_K_M, Dolphin3.0-R1-Mistral-24B is the smaller download — 13,070,715,520 bytes against 18,556,685,824. At long context the gap widens: Qwen3-30B-A3B-Thinking-2507's KV cache at 32K is 1.7× smaller, which usually matters more than the difference in weights.

From the file· summed bytes, KV per layer

Side by side

	Dolphin3.0-R1-Mistral-24B	Qwen3-30B-A3B-Thinking-2507
Parameters	23.6B	30.5B
Architecture	llama	qwen3moe
Layers	40	48
Native context	32,768	262,144
Mixture of experts	no	yes, 128 experts
Quantizations published	38	51
Smallest quantization	6.10 GiB	7.05 GiB
Q4_K_M	12.17 GiB	17.28 GiB
Licence	—	apache-2.0

KV cache by context

the term that decides long-context viability

Context	Dolphin3.0-R1-Mistral-24B	Qwen3-30B-A3B-Thinking-2507	Ratio
4,096	0.63 GiB	0.38 GiB	1.67×
8,192	1.25 GiB	0.75 GiB	1.67×
16,384	2.50 GiB	1.50 GiB	1.67×
32,768	5.00 GiB	3.00 GiB	1.67×
65,536	10.00 GiB	6.00 GiB	1.67×
131,072	20.00 GiB	12.00 GiB	1.67×