Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Sibling matchup inside the o1 family.
o1
59
o1-pro
30
o1 makes more sense if you want the cheaper token bill, while o1-pro is the cleaner fit if knowledge is the priority.
Knowledge
+3.3 difference
o1
o1-pro
$15 / $60
$150 / $600
98 t/s
N/A
32.29s
N/A
200K
200K
o1 makes more sense if you want the cheaper token bill, while o1-pro is the cleaner fit if knowledge is the priority.
o1 and o1-pro sit in the same o1 family. This page is less about two unrelated model lineages and more about how the siblings trade off on benchmark shape, token costs, and practical limits like context window.
o1 is clearly ahead on the provisional aggregate, 59 to 30. 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 $15.00 input / $60.00 output per 1M tokens for o1. That is roughly 10.0x on output cost alone.
o1 and o1-pro are sibling variants in the o1 family, so the right pick depends on whether you value the better benchmark line, cheaper tokens, or the larger context window. o1 is ahead on BenchLM's provisional leaderboard 59 to 30.
o1-pro has the edge for knowledge tasks in this comparison, averaging 79 versus 75.7. Inside this category, GPQA is the benchmark that creates the most daylight between them.
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