o1 vs Qwen3.5 397B

Pick Qwen3.5 397B if you want the stronger benchmark profile. o1 only becomes the better choice if knowledge is the priority or you need the larger 200K context window.

Qwen3.5 397B is clearly ahead on the provisional aggregate, 64 to 58. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

Qwen3.5 397B's sharpest advantage is in instruction following, where it averages 92.6 against 92.2. The single biggest benchmark swing on the page is GPQA, 75.7% to 88.4%. o1 does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.

o1 is also the more expensive model on tokens at $15.00 input / $60.00 output per 1M tokens, versus $0.60 input / $3.60 output per 1M tokens for Qwen3.5 397B. That is roughly 16.7x on output cost alone. o1 is the reasoning model in the pair, while Qwen3.5 397B is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. o1 gives you the larger context window at 200K, compared with 128K for Qwen3.5 397B.