Is ChatGPT-5 or Qwen3-1.7B smaller?

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

Which uses less memory at long context?

ChatGPT-5 — its KV cache at 32K context is 9.3x smaller, because of how its attention layers cache.

Model comparison

ChatGPT-5 vs Qwen3-1.7B

These two publish different quantization sets; the table below has the exact sizes. At long context the gap widens: ChatGPT-5's KV cache at 32K is 9.3× smaller, which usually matters more than the difference in weights.

From the file· summed bytes, KV per layer

Side by side

	ChatGPT-5	Qwen3-1.7B
Parameters	494M	2.0B
Architecture	qwen2	qwen3
Layers	24	28
Native context	32,768	40,960
Mixture of experts	no	no
Quantizations published	1	48
Smallest quantization	0.49 GiB	0.50 GiB
Q4_K_M	—	1.03 GiB
Licence	apache-2.0	—

KV cache by context

the term that decides long-context viability

Context	ChatGPT-5	Qwen3-1.7B	Ratio
4,096	0.05 GiB	0.44 GiB	9.33×
8,192	0.09 GiB	0.88 GiB	9.33×
16,384	0.19 GiB	1.75 GiB	9.33×
32,768	0.38 GiB	3.50 GiB	9.33×
65,536	0.75 GiB	7.00 GiB	9.33×
131,072	1.50 GiB	14.00 GiB	9.33×