Is Qwen3-Coder-30B-A3B-Instruct or LFM2-24B-A2B smaller?

LFM2-24B-A2B is smaller at Q4_K_M: 13.43 GiB against 17.28 GiB.

Which uses less memory at long context?

LFM2-24B-A2B — its KV cache at 32K context is 4.8x smaller, because of how its attention layers cache.

Model comparison

Qwen3-Coder-30B-A3B-Instruct vs LFM2-24B-A2B

At Q4_K_M, LFM2-24B-A2B is the smaller download — 14,415,473,952 bytes against 18,556,689,568. At long context the gap widens: LFM2-24B-A2B's KV cache at 32K is 4.8× smaller, which usually matters more than the difference in weights.

From the file· summed bytes, KV per layer

Side by side

	Qwen3-Coder-30B-A3B-Instruct	LFM2-24B-A2B
Parameters	30.5B	23.8B
Architecture	qwen3moe	lfm2moe
Layers	48	40
Native context	262,144	128,000
Mixture of experts	yes, 128 experts	yes, 64 experts
Quantizations published	46	33
Smallest quantization	7.46 GiB	5.35 GiB
Q4_K_M	17.28 GiB	13.43 GiB
Licence	apache-2.0	other

KV cache by context

the term that decides long-context viability

Context	Qwen3-Coder-30B-A3B-Instruct	LFM2-24B-A2B	Ratio
4,096	0.38 GiB	0.08 GiB	4.80×
8,192	0.75 GiB	0.16 GiB	4.80×
16,384	1.50 GiB	0.31 GiB	4.80×
32,768	3.00 GiB	0.63 GiB	4.80×
65,536	6.00 GiB	1.25 GiB	4.80×
131,072	12.00 GiB	2.50 GiB	4.80×