Is Qwen3-Zero-Coder-Reasoning-0.8B or gemma-4-E4B-it smaller?

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

Which uses less memory at long context?

gemma-4-E4B-it — its KV cache at 32K context is 10.4x smaller, because of how its attention layers cache.

Model comparison

Qwen3-Zero-Coder-Reasoning-0.8B vs gemma-4-E4B-it

These two publish different quantization sets; the table below has the exact sizes. At long context the gap widens: gemma-4-E4B-it's KV cache at 32K is 10.4× 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-0.8B	gemma-4-E4B-it
Parameters	816M	8.0B
Architecture	qwen3	gemma4
Layers	42	42
Native context	40,960	131,072
Mixture of experts	no	no
Quantizations published	3	36
Smallest quantization	2.33 GiB	3.30 GiB
Q4_K_M	—	4.64 GiB
Licence	apache-2.0	apache-2.0

KV cache by context

the term that decides long-context viability

Context	Qwen3-Zero-Coder-Reasoning-0.8B	gemma-4-E4B-it	Ratio
4,096	0.66 GiB	0.12 GiB	5.33×
8,192	1.31 GiB	0.18 GiB	7.38×
16,384	2.63 GiB	0.29 GiB	9.14×
32,768	5.25 GiB	0.51 GiB	10.38×
65,536	10.50 GiB	0.94 GiB	11.13×
131,072	21.00 GiB	1.82 GiB	11.55×