Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Gemini 3.1 Pro
94
MiMo-V2.5
74
Pick Gemini 3.1 Pro if you want the stronger benchmark profile. MiMo-V2.5 only becomes the better choice if you want the cheaper token bill or you want the stronger reasoning-first profile.
Multimodal
+6.0 difference
Gemini 3.1 Pro
MiMo-V2.5
$1.25 / $5
$0.4 / $2
109 t/s
N/A
29.71s
N/A
1M
1M
Pick Gemini 3.1 Pro if you want the stronger benchmark profile. MiMo-V2.5 only becomes the better choice if you want the cheaper token bill or you want the stronger reasoning-first profile.
Gemini 3.1 Pro is clearly ahead on the provisional aggregate, 94 to 74. 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 77.9. The single biggest benchmark swing on the page is MMMU-Pro, 83.9% to 77.9%.
Gemini 3.1 Pro is also the more expensive model on tokens at $1.25 input / $5.00 output per 1M tokens, versus $0.40 input / $2.00 output per 1M tokens for MiMo-V2.5. That is roughly 2.5x on output cost alone. MiMo-V2.5 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 is ahead on BenchLM's provisional leaderboard, 94 to 74. The biggest single separator in this matchup is MMMU-Pro, where the scores are 83.9% and 77.9%.
Gemini 3.1 Pro has the edge for multimodal and grounded tasks in this comparison, averaging 83.9 versus 77.9. Inside this category, MMMU-Pro is the benchmark that creates the most daylight between them.
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