Is glm-4-9b-chat-1m or Qwen3-Coder-30B-A3B-Instruct smaller?

glm-4-9b-chat-1m is smaller at Q4_K_M: 5.88 GiB against 17.28 GiB.

Which uses less memory at long context?

Qwen3-Coder-30B-A3B-Instruct — its KV cache at 32K context is 6.7x smaller, because of how its attention layers cache.

Model comparison

glm-4-9b-chat-1m vs Qwen3-Coder-30B-A3B-Instruct

At Q4_K_M, glm-4-9b-chat-1m is the smaller download — 6,308,679,680 bytes against 18,556,689,568. At long context the gap widens: Qwen3-Coder-30B-A3B-Instruct's KV cache at 32K is 6.7× smaller, which usually matters more than the difference in weights.

From the file· summed bytes, KV per layer

Side by side

	glm-4-9b-chat-1m	Qwen3-Coder-30B-A3B-Instruct
Parameters	9.5B	30.5B
Architecture	chatglm	qwen3moe
Layers	40	48
Native context	—	262,144
Mixture of experts	no	yes, 128 experts
Quantizations published	49	46
Smallest quantization	3.69 GiB	7.46 GiB
Q4_K_M	5.88 GiB	17.28 GiB
Licence	other	apache-2.0

KV cache by context

the term that decides long-context viability

Context	glm-4-9b-chat-1m	Qwen3-Coder-30B-A3B-Instruct	Ratio
4,096	2.50 GiB	0.38 GiB	6.67×
8,192	5.00 GiB	0.75 GiB	6.67×
16,384	10.00 GiB	1.50 GiB	6.67×
32,768	20.00 GiB	3.00 GiB	6.67×
65,536	40.00 GiB	6.00 GiB	6.67×
131,072	80.00 GiB	12.00 GiB	6.67×