Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Kimi K2.5
64
o1-pro
29
Verified leaderboard positions: Kimi K2.5 #11 · o1-pro unranked
Pick Kimi K2.5 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
+13.9 difference
Kimi K2.5
o1-pro
$0.6 / $3
$150 / $600
45 t/s
N/A
2.38s
N/A
256K
200K
Pick Kimi K2.5 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.
Kimi K2.5 is clearly ahead on the provisional aggregate, 64 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 $0.60 input / $3.00 output per 1M tokens for Kimi K2.5. That is roughly 200.0x on output cost alone. o1-pro is the reasoning model in the pair, while Kimi K2.5 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. Kimi K2.5 gives you the larger context window at 256K, compared with 200K for o1-pro.
Kimi K2.5 is ahead on BenchLM's provisional leaderboard, 64 to 29. The biggest single separator in this matchup is GPQA, where the scores are 87.6% and 79%.
o1-pro has the edge for knowledge tasks in this comparison, averaging 79 versus 65.1. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Estimates at 50,000 req/day · 1000 tokens/req average.
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