Is Qwen3.6-27B-Ablit or Qwen3-Coder-30B-A3B-Instruct smaller?

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

Which uses less memory at long context?

Qwen3.6-27B-Ablit — its KV cache at 32K context is 1.5x smaller, because of how its attention layers cache.

Model comparison

Qwen3.6-27B-Ablit vs Qwen3-Coder-30B-A3B-Instruct

These two publish different quantization sets; the table below has the exact sizes. At long context the gap widens: Qwen3.6-27B-Ablit's KV cache at 32K is 1.5× smaller, which usually matters more than the difference in weights.

From the file· summed bytes, KV per layer

Side by side

	Qwen3.6-27B-Ablit	Qwen3-Coder-30B-A3B-Instruct
Parameters	26.9B	30.5B
Architecture	qwen35	qwen3moe
Layers	64	48
Native context	262,144	262,144
Mixture of experts	no	yes, 128 experts
Quantizations published	2	46
Smallest quantization	7.85 GiB	7.46 GiB
Q4_K_M	—	17.28 GiB
Licence	—	apache-2.0

KV cache by context

the term that decides long-context viability

Context	Qwen3.6-27B-Ablit	Qwen3-Coder-30B-A3B-Instruct	Ratio
4,096	0.25 GiB	0.38 GiB	1.50×
8,192	0.50 GiB	0.75 GiB	1.50×
16,384	1.00 GiB	1.50 GiB	1.50×
32,768	2.00 GiB	3.00 GiB	1.50×
65,536	4.00 GiB	6.00 GiB	1.50×
131,072	8.00 GiB	12.00 GiB	1.50×