Is CHEETAH-350M-Merged-FP16 or Qwen3-0.6B smaller?

CHEETAH-350M-Merged-FP16 is smaller at Q4_K_M: 0.22 GiB against 0.37 GiB.

Which uses less memory at long context?

CHEETAH-350M-Merged-FP16 — its KV cache at 32K context is 9.3x smaller, because of how its attention layers cache.

Model comparison

CHEETAH-350M-Merged-FP16 vs Qwen3-0.6B

At Q4_K_M, CHEETAH-350M-Merged-FP16 is the smaller download — 231,031,616 bytes against 396,705,472. At long context the gap widens: CHEETAH-350M-Merged-FP16's KV cache at 32K is 9.3× smaller, which usually matters more than the difference in weights.

From the file· summed bytes, KV per layer

Side by side

	CHEETAH-350M-Merged-FP16	Qwen3-0.6B
Parameters	354M	752M
Architecture	lfm2	qwen3
Layers	16	28
Native context	128,000	40,960
Mixture of experts	no	no
Quantizations published	47	44
Smallest quantization	0.10 GiB	0.20 GiB
Q4_K_M	0.22 GiB	0.37 GiB
Licence	other	—

KV cache by context

the term that decides long-context viability

Context	CHEETAH-350M-Merged-FP16	Qwen3-0.6B	Ratio
4,096	0.05 GiB	0.44 GiB	9.33×
8,192	0.09 GiB	0.88 GiB	9.33×
16,384	0.19 GiB	1.75 GiB	9.33×
32,768	0.38 GiB	3.50 GiB	9.33×
65,536	0.75 GiB	7.00 GiB	9.33×
131,072	1.50 GiB	14.00 GiB	9.33×