Is Qwen3.5-27B-Engineer-Deckard-Gemini or gemma-4-12B-it-qat-q4_0-unquantized smaller?

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

Which uses less memory at long context?

Qwen3.5-27B-Engineer-Deckard-Gemini — its KV cache at 32K context is 1.2x smaller, because of how its attention layers cache.

Model comparison

Qwen3.5-27B-Engineer-Deckard-Gemini vs gemma-4-12B-it-qat-q4_0-unquantized

These two publish different quantization sets; the table below has the exact sizes. At long context the gap widens: Qwen3.5-27B-Engineer-Deckard-Gemini'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

	Qwen3.5-27B-Engineer-Deckard-Gemini	gemma-4-12B-it-qat-q4_0-unquantized
Parameters	27.7B	12.0B
Architecture	qwen35	gemma4
Layers	64	48
Native context	262,144	262,144
Mixture of experts	no	no
Quantizations published	23	2
Smallest quantization	5.80 GiB	6.50 GiB
Q4_K_M	—	—
Licence	apache-2.0	apache-2.0

KV cache by context

the term that decides long-context viability

Context	Qwen3.5-27B-Engineer-Deckard-Gemini	gemma-4-12B-it-qat-q4_0-unquantized	Ratio
4,096	0.25 GiB	0.72 GiB	2.87×
8,192	0.50 GiB	0.97 GiB	1.94×
16,384	1.00 GiB	1.47 GiB	1.47×
32,768	2.00 GiB	2.47 GiB	1.23×
65,536	4.00 GiB	4.47 GiB	1.12×
131,072	8.00 GiB	8.47 GiB	1.06×