Is gemma-3-12b-it-qat or Qwen3-30B-A3B-Thinking-2507 smaller?

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

Which uses less memory at long context?

gemma-3-12b-it-qat — its KV cache at 32K context is 1.2x smaller, because of how its attention layers cache.

Model comparison

gemma-3-12b-it-qat vs Qwen3-30B-A3B-Thinking-2507

These two publish different quantization sets; the table below has the exact sizes. At long context the gap widens: gemma-3-12b-it-qat's KV cache at 32K is 1.2× smaller, which usually matters more than the difference in weights.

From the file· summed bytes, KV per layer

Side by side

	gemma-3-12b-it-qat	Qwen3-30B-A3B-Thinking-2507
Parameters	11.8B	30.5B
Architecture	gemma3	qwen3moe
Layers	48	48
Native context	131,072	262,144
Mixture of experts	no	yes, 128 experts
Quantizations published	1	51
Smallest quantization	6.64 GiB	7.05 GiB
Q4_K_M	—	17.28 GiB
Licence	—	apache-2.0

KV cache by context

the term that decides long-context viability

Context	gemma-3-12b-it-qat	Qwen3-30B-A3B-Thinking-2507	Ratio
4,096	0.72 GiB	0.38 GiB	1.92×
8,192	0.97 GiB	0.75 GiB	1.29×
16,384	1.47 GiB	1.50 GiB	1.02×
32,768	2.47 GiB	3.00 GiB	1.22×
65,536	4.47 GiB	6.00 GiB	1.34×
131,072	8.47 GiB	12.00 GiB	1.42×