Is gemma-4-12B-it-qat-q4_0-unquantized or Hunyuan-A13B-Instruct smaller?

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

Which uses less memory at long context?

gemma-4-12B-it-qat-q4_0-unquantized — its KV cache at 32K context is 1.6x smaller, because of how its attention layers cache.

Model comparison

gemma-4-12B-it-qat-q4_0-unquantized vs Hunyuan-A13B-Instruct

These two publish different quantization sets; the table below has the exact sizes. At long context the gap widens: gemma-4-12B-it-qat-q4_0-unquantized's KV cache at 32K is 1.6× smaller, which usually matters more than the difference in weights.

From the file· summed bytes, KV per layer

Side by side

	gemma-4-12B-it-qat-q4_0-unquantized	Hunyuan-A13B-Instruct
Parameters	12.0B	80.4B
Architecture	gemma4	hunyuan-moe
Layers	48	32
Native context	262,144	32,768
Mixture of experts	no	yes, 64 experts
Quantizations published	2	70
Smallest quantization	6.50 GiB	15.18 GiB
Q4_K_M	—	45.43 GiB
Licence	apache-2.0	other

KV cache by context

the term that decides long-context viability

Context	gemma-4-12B-it-qat-q4_0-unquantized	Hunyuan-A13B-Instruct	Ratio
4,096	0.72 GiB	0.50 GiB	1.44×
8,192	0.97 GiB	1.00 GiB	1.03×
16,384	1.47 GiB	2.00 GiB	1.36×
32,768	2.47 GiB	4.00 GiB	1.62×
65,536	4.47 GiB	8.00 GiB	1.79×
131,072	8.47 GiB	16.00 GiB	1.89×