Is Qwen2.5-Coder-1.5B-Unsensored-DPO or Qwen3-1.7B smaller?

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

Which uses less memory at long context?

Qwen2.5-Coder-1.5B-Unsensored-DPO — its KV cache at 32K context is 4.0x smaller, because of how its attention layers cache.

Model comparison

Qwen2.5-Coder-1.5B-Unsensored-DPO vs Qwen3-1.7B

These two publish different quantization sets; the table below has the exact sizes. At long context the gap widens: Qwen2.5-Coder-1.5B-Unsensored-DPO'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

	Qwen2.5-Coder-1.5B-Unsensored-DPO	Qwen3-1.7B
Parameters	1.5B	2.0B
Architecture	qwen2	qwen3
Layers	28	28
Native context	32,768	40,960
Mixture of experts	no	no
Quantizations published	48	48
Smallest quantization	0.41 GiB	0.50 GiB
Q4_K_M	—	1.03 GiB
Licence	—	—

KV cache by context

the term that decides long-context viability

Context	Qwen2.5-Coder-1.5B-Unsensored-DPO	Qwen3-1.7B	Ratio
4,096	0.11 GiB	0.44 GiB	4.00×
8,192	0.22 GiB	0.88 GiB	4.00×
16,384	0.44 GiB	1.75 GiB	4.00×
32,768	0.88 GiB	3.50 GiB	4.00×
65,536	1.75 GiB	7.00 GiB	4.00×
131,072	3.50 GiB	14.00 GiB	4.00×