Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemini 2.5 Pro
67
Kimi K2.5 (Reasoning)
79
Pick Kimi K2.5 (Reasoning) if you want the stronger benchmark profile. Gemini 2.5 Pro only becomes the better choice if you need the larger 1M context window or you would rather avoid the extra latency and token burn of a reasoning model.
Coding
+13.0 difference
Knowledge
+46.5 difference
Gemini 2.5 Pro
Kimi K2.5 (Reasoning)
$1.25 / $5
$null / $null
117 t/s
N/A
21.19s
N/A
1M
128K
Pick Kimi K2.5 (Reasoning) if you want the stronger benchmark profile. Gemini 2.5 Pro only becomes the better choice if you need the larger 1M context window or you would rather avoid the extra latency and token burn of a reasoning model.
Kimi K2.5 (Reasoning) is clearly ahead on the provisional aggregate, 79 to 67. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Kimi K2.5 (Reasoning)'s sharpest advantage is in knowledge, where it averages 87.3 against 40.8. The single biggest benchmark swing on the page is SWE-bench Verified, 63.8% to 76.8%.
Kimi K2.5 (Reasoning) 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 128K for Kimi K2.5 (Reasoning).
Kimi K2.5 (Reasoning) is ahead on BenchLM's provisional leaderboard, 79 to 67. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 63.8% and 76.8%.
Kimi K2.5 (Reasoning) has the edge for knowledge tasks in this comparison, averaging 87.3 versus 40.8. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Kimi K2.5 (Reasoning) has the edge for coding in this comparison, averaging 76.8 versus 63.8. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
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