Is Qwen3-Zero-Coder-Reasoning-V2-0.8B or gemma-3-1b-it smaller?

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

Which uses less memory at long context?

gemma-3-1b-it — its KV cache at 32K context is 35.8x smaller, because of how its attention layers cache.

Model comparison

Qwen3-Zero-Coder-Reasoning-V2-0.8B vs gemma-3-1b-it

These two publish different quantization sets; the table below has the exact sizes. At long context the gap widens: gemma-3-1b-it's KV cache at 32K is 35.8× smaller, which usually matters more than the difference in weights.

From the file· summed bytes, KV per layer

Side by side

	Qwen3-Zero-Coder-Reasoning-V2-0.8B	gemma-3-1b-it
Parameters	816M	1000M
Architecture	qwen3	gemma3
Layers	42	26
Native context	40,960	32,768
Mixture of experts	no	no
Quantizations published	26	28
Smallest quantization	0.24 GiB	0.52 GiB
Q4_K_M	—	0.75 GiB
Licence	apache-2.0	gemma

KV cache by context

the term that decides long-context viability

Context	Qwen3-Zero-Coder-Reasoning-V2-0.8B	gemma-3-1b-it	Ratio
4,096	0.66 GiB	0.04 GiB	17.68×
8,192	1.31 GiB	0.05 GiB	24.89×
16,384	2.63 GiB	0.08 GiB	31.26×
32,768	5.25 GiB	0.15 GiB	35.84×
65,536	10.50 GiB	0.27 GiB	38.68×
131,072	21.00 GiB	0.52 GiB	40.27×