Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
o1-pro
29
Qwen3 235B 2507
34
Pick Qwen3 235B 2507 if you want the stronger benchmark profile. o1-pro only becomes the better choice if knowledge is the priority or you need the larger 200K context window.
Knowledge
+2.8 difference
o1-pro
Qwen3 235B 2507
$150 / $600
$0 / $0
N/A
N/A
N/A
N/A
200K
128K
Pick Qwen3 235B 2507 if you want the stronger benchmark profile. o1-pro only becomes the better choice if knowledge is the priority or you need the larger 200K context window.
Qwen3 235B 2507 is clearly ahead on the provisional aggregate, 34 to 29. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
o1-pro is also the more expensive model on tokens at $150.00 input / $600.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Qwen3 235B 2507. That is roughly Infinityx on output cost alone. o1-pro is the reasoning model in the pair, while Qwen3 235B 2507 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-pro gives you the larger context window at 200K, compared with 128K for Qwen3 235B 2507.
Qwen3 235B 2507 is ahead on BenchLM's provisional leaderboard, 34 to 29. The biggest single separator in this matchup is GPQA, where the scores are 79% and 77.5%.
o1-pro has the edge for knowledge tasks in this comparison, averaging 79 versus 76.2. Inside this category, GPQA is the benchmark that creates the most daylight between them.
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