Is Qwen3-Coder-Next-Opus-4.6-Reasoning-Distilled or gemma-3-1b-it smaller?

gemma-3-1b-it is smaller at Q4_K_M: 0.75 GiB against 45.16 GiB.

Which uses less memory at long context?

gemma-3-1b-it — its KV cache at 32K context is 5.1x smaller, because of how its attention layers cache.

Model comparison

Qwen3-Coder-Next-Opus-4.6-Reasoning-Distilled vs gemma-3-1b-it

At Q4_K_M, gemma-3-1b-it is the smaller download — 806,058,240 bytes against 48,489,047,936. At long context the gap widens: gemma-3-1b-it's KV cache at 32K is 5.1× smaller, which usually matters more than the difference in weights.

From the file· summed bytes, KV per layer

Side by side

	Qwen3-Coder-Next-Opus-4.6-Reasoning-Distilled	gemma-3-1b-it
Parameters	—	1000M
Architecture	qwen3next	gemma3
Layers	48	26
Native context	262,144	32,768
Mixture of experts	yes, 512 experts	no
Quantizations published	21	28
Smallest quantization	0.38 GiB	0.52 GiB
Q4_K_M	45.16 GiB	0.75 GiB
Licence	apache-2.0	gemma

KV cache by context

the term that decides long-context viability

Context	Qwen3-Coder-Next-Opus-4.6-Reasoning-Distilled	gemma-3-1b-it	Ratio
4,096	0.09 GiB	0.04 GiB	2.53×
8,192	0.19 GiB	0.05 GiB	3.56×
16,384	0.38 GiB	0.08 GiB	4.47×
32,768	0.75 GiB	0.15 GiB	5.12×
65,536	1.50 GiB	0.27 GiB	5.53×
131,072	3.00 GiB	0.52 GiB	5.75×