Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemini 2.5 Pro
65
o1-pro
29
Pick Gemini 2.5 Pro if you want the stronger benchmark profile. o1-pro only becomes the better choice if knowledge is the priority or you want the stronger reasoning-first profile.
Knowledge
+38.2 difference
Gemini 2.5 Pro
o1-pro
$1.25 / $10
$150 / $600
117 t/s
N/A
21.19s
N/A
1M
200K
Pick Gemini 2.5 Pro if you want the stronger benchmark profile. o1-pro only becomes the better choice if knowledge is the priority or you want the stronger reasoning-first profile.
Gemini 2.5 Pro is clearly ahead on the provisional aggregate, 65 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 $1.25 input / $10.00 output per 1M tokens for Gemini 2.5 Pro. That is roughly 60.0x on output cost alone. o1-pro is the reasoning model in the pair, while Gemini 2.5 Pro 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. Gemini 2.5 Pro gives you the larger context window at 1M, compared with 200K for o1-pro.
Gemini 2.5 Pro is ahead on BenchLM's provisional leaderboard, 65 to 29. The biggest single separator in this matchup is GPQA, where the scores are 83% and 79%.
o1-pro has the edge for knowledge tasks in this comparison, averaging 79 versus 40.8. Inside this category, GPQA is the benchmark that creates the most daylight between them.
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