Is GLM-4.1V-9B-Thinking or gemma-4-12B-it smaller?

GLM-4.1V-9B-Thinking is smaller at Q4_K_M: 5.74 GiB against 6.63 GiB.

Which uses less memory at long context?

GLM-4.1V-9B-Thinking — its KV cache at 32K context is 2.0x smaller, because of how its attention layers cache.

Model comparison

GLM-4.1V-9B-Thinking vs gemma-4-12B-it

At Q4_K_M, GLM-4.1V-9B-Thinking is the smaller download — 6,166,574,432 bytes against 7,121,861,440. At long context the gap widens: GLM-4.1V-9B-Thinking's KV cache at 32K is 2.0× smaller, which usually matters more than the difference in weights.

From the file· summed bytes, KV per layer

Side by side

	GLM-4.1V-9B-Thinking	gemma-4-12B-it
Parameters	10.3B	12.0B
Architecture	glm4	gemma4
Layers	40	48
Native context	65,536	262,144
Mixture of experts	no	no
Quantizations published	43	59
Smallest quantization	2.98 GiB	3.92 GiB
Q4_K_M	5.74 GiB	6.63 GiB
Licence	mit	apache-2.0

KV cache by context

the term that decides long-context viability

Context	GLM-4.1V-9B-Thinking	gemma-4-12B-it	Ratio
4,096	0.16 GiB	0.72 GiB	4.60×
8,192	0.31 GiB	0.97 GiB	3.10×
16,384	0.63 GiB	1.47 GiB	2.35×
32,768	1.25 GiB	2.47 GiB	1.98×
65,536	2.50 GiB	4.47 GiB	1.79×
131,072	5.00 GiB	8.47 GiB	1.69×