Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Claude Opus 4.7 (Adaptive)
90
o1-pro
29
Verified leaderboard positions: Claude Opus 4.7 (Adaptive) #5 · o1-pro unranked
Pick Claude Opus 4.7 (Adaptive) if you want the stronger benchmark profile. o1-pro only becomes the better choice if knowledge is the priority.
Knowledge
+10.8 difference
Claude Opus 4.7 (Adaptive)
o1-pro
$5 / $25
$150 / $600
N/A
N/A
N/A
N/A
1M
200K
Pick Claude Opus 4.7 (Adaptive) if you want the stronger benchmark profile. o1-pro only becomes the better choice if knowledge is the priority.
Claude Opus 4.7 (Adaptive) is clearly ahead on the provisional aggregate, 90 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 $5.00 input / $25.00 output per 1M tokens for Claude Opus 4.7 (Adaptive). That is roughly 24.0x on output cost alone. Claude Opus 4.7 (Adaptive) gives you the larger context window at 1M, compared with 200K for o1-pro.
Claude Opus 4.7 (Adaptive) is ahead on BenchLM's provisional leaderboard, 90 to 29. The biggest single separator in this matchup is GPQA, where the scores are 94.2% and 79%.
o1-pro has the edge for knowledge tasks in this comparison, averaging 79 versus 68.2. Inside this category, GPQA is the benchmark that creates the most daylight between them.
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