Is Precog-24B-v1 or Qwen3-30B-A3B-Thinking-2507 smaller?

Precog-24B-v1 is smaller at Q4_K_M: 13.35 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

Precog-24B-v1 vs Qwen3-30B-A3B-Thinking-2507

At Q4_K_M, Precog-24B-v1 is the smaller download — 14,333,912,608 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

	Precog-24B-v1	Qwen3-30B-A3B-Thinking-2507
Parameters	—	30.5B
Architecture	llama	qwen3moe
Layers	40	48
Native context	131,072	262,144
Mixture of experts	no	yes, 128 experts
Quantizations published	59	51
Smallest quantization	4.91 GiB	7.05 GiB
Q4_K_M	13.35 GiB	17.28 GiB
Licence	—	apache-2.0

KV cache by context

the term that decides long-context viability

Context	Precog-24B-v1	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×