Is LFM2.5-Queen-Opus-4.7-8B-A1B or Qwen3-8B smaller?

Both publish quantizations; compare the table for the exact sizes.

Which uses less memory at long context?

LFM2.5-Queen-Opus-4.7-8B-A1B — its KV cache at 32K context is 12.0x smaller, because of how its attention layers cache.

Model comparison

LFM2.5-Queen-Opus-4.7-8B-A1B vs Qwen3-8B

These two publish different quantization sets; the table below has the exact sizes. At long context the gap widens: LFM2.5-Queen-Opus-4.7-8B-A1B's KV cache at 32K is 12.0× smaller, which usually matters more than the difference in weights.

From the file· summed bytes, KV per layer

Side by side

	LFM2.5-Queen-Opus-4.7-8B-A1B	Qwen3-8B
Parameters	8.5B	8.2B
Architecture	lfm2moe	qwen3
Layers	24	36
Native context	128,000	40,960
Mixture of experts	yes, 32 experts	no
Quantizations published	24	51
Smallest quantization	1.70 GiB	2.12 GiB
Q4_K_M	—	4.68 GiB
Licence	other	apache-2.0

KV cache by context

the term that decides long-context viability

Context	LFM2.5-Queen-Opus-4.7-8B-A1B	Qwen3-8B	Ratio
4,096	0.05 GiB	0.56 GiB	11.99×
8,192	0.09 GiB	1.13 GiB	12.00×
16,384	0.19 GiB	2.25 GiB	12.00×
32,768	0.38 GiB	4.50 GiB	12.00×
65,536	0.75 GiB	9.00 GiB	12.00×
131,072	1.50 GiB	18.00 GiB	12.00×