Is Gemma-4-E4B-Luchador-Rudo or Qwen3.8-27B smaller?

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

Which uses less memory at long context?

Gemma-4-E4B-Luchador-Rudo — its KV cache at 32K context is 4.0x smaller, because of how its attention layers cache.

Model comparison

Gemma-4-E4B-Luchador-Rudo vs Qwen3.8-27B

These two publish different quantization sets; the table below has the exact sizes. At long context the gap widens: Gemma-4-E4B-Luchador-Rudo's KV cache at 32K is 4.0× smaller, which usually matters more than the difference in weights.

From the file· summed bytes, KV per layer

Side by side

	Gemma-4-E4B-Luchador-Rudo	Qwen3.8-27B
Parameters	8.0B	27.8B
Architecture	gemma4	qwen35
Layers	42	64
Native context	131,072	262,144
Mixture of experts	no	no
Quantizations published	15	22
Smallest quantization	4.10 GiB	8.39 GiB
Q4_K_M	—	15.66 GiB
Licence	gemma	apache-2.0

KV cache by context

the term that decides long-context viability

Context	Gemma-4-E4B-Luchador-Rudo	Qwen3.8-27B	Ratio
4,096	0.12 GiB	0.25 GiB	2.03×
8,192	0.18 GiB	0.50 GiB	2.81×
16,384	0.29 GiB	1.00 GiB	3.48×
32,768	0.51 GiB	2.00 GiB	3.95×
65,536	0.94 GiB	4.00 GiB	4.24×
131,072	1.82 GiB	8.00 GiB	4.40×