Is UI-TARS-1.5-7B 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?

UI-TARS-1.5-7B — its KV cache at 32K context is 1.4x smaller, because of how its attention layers cache.

Model comparison

UI-TARS-1.5-7B 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: UI-TARS-1.5-7B's KV cache at 32K is 1.4× smaller, which usually matters more than the difference in weights.

From the file· summed bytes, KV per layer

Side by side

	UI-TARS-1.5-7B	gemma-4-12B-it-qat-q4_0-unquantized
Parameters	8.3B	12.0B
Architecture	qwen2vl	gemma4
Layers	28	48
Native context	128,000	262,144
Mixture of experts	no	no
Quantizations published	14	2
Smallest quantization	2.81 GiB	6.50 GiB
Q4_K_M	4.36 GiB	—
Licence	—	apache-2.0

KV cache by context

the term that decides long-context viability

Context	UI-TARS-1.5-7B	gemma-4-12B-it-qat-q4_0-unquantized	Ratio
4,096	0.22 GiB	0.72 GiB	3.29×
8,192	0.44 GiB	0.97 GiB	2.21×
16,384	0.88 GiB	1.47 GiB	1.68×
32,768	1.75 GiB	2.47 GiB	1.41×
65,536	3.50 GiB	4.47 GiB	1.28×
131,072	7.00 GiB	8.47 GiB	1.21×