Is Qwen3.5-9B-gemini-3.1-opus-4.6-reasoning or HyperCLOVAX-SEED-Text-Instruct-1.5B smaller?

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

Which uses less memory at long context?

We cannot resolve the KV layout for one of these models, so we do not publish a comparison.

Model comparison

These two publish different quantization sets; the table below has the exact sizes.

From the file· summed bytes, KV per layer

	Qwen3.5-9B-gemini-3.1-opus-4.6-reasoning	HyperCLOVAX-SEED-Text-Instruct-1.5B
Parameters	9.4B	1.6B
Architecture	qwen35	llama
Layers	32	—
Native context	262,144	—
Mixture of experts	no	no
Quantizations published	24	1
Smallest quantization	2.28 GiB	1.06 GiB
Q4_K_M	—	1.06 GiB
Licence	apache-2.0	other

the term that decides long-context viability

Context	Qwen3.5-9B-gemini-3.1-opus-4.6-reasoning	HyperCLOVAX-SEED-Text-Instruct-1.5B	Ratio
4,096	0.13 GiB	—	—
8,192	0.25 GiB	—	—
16,384	0.50 GiB	—	—
32,768	1.00 GiB	—	—
65,536	2.00 GiB	—	—
131,072	4.00 GiB	—	—