Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemini 3.1 Pro
93
Kimi K2.5 (Reasoning)
79
Pick Gemini 3.1 Pro if you want the stronger benchmark profile. Kimi K2.5 (Reasoning) only becomes the better choice if you want the stronger reasoning-first profile.
Multimodal
+5.4 difference
Gemini 3.1 Pro
Kimi K2.5 (Reasoning)
$1.25 / $5
$null / $null
109 t/s
N/A
29.71s
N/A
1M
128K
Pick Gemini 3.1 Pro if you want the stronger benchmark profile. Kimi K2.5 (Reasoning) only becomes the better choice if you want the stronger reasoning-first profile.
Gemini 3.1 Pro is clearly ahead on the provisional aggregate, 93 to 79. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Gemini 3.1 Pro's sharpest advantage is in multimodal & grounded, where it averages 83.9 against 78.5. The single biggest benchmark swing on the page is MMMU-Pro, 83.9% to 78.5%.
Kimi K2.5 (Reasoning) is the reasoning model in the pair, while Gemini 3.1 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 3.1 Pro gives you the larger context window at 1M, compared with 128K for Kimi K2.5 (Reasoning).
Gemini 3.1 Pro is ahead on BenchLM's provisional leaderboard, 93 to 79. The biggest single separator in this matchup is MMMU-Pro, where the scores are 83.9% and 78.5%.
Gemini 3.1 Pro has the edge for multimodal and grounded tasks in this comparison, averaging 83.9 versus 78.5. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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