Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
MiMo-V2-Omni
84
MiniMax M2.7
53
Pick MiMo-V2-Omni if you want the stronger benchmark profile. MiniMax M2.7 only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Coding
+21.1 difference
MiMo-V2-Omni
MiniMax M2.7
N/A
$0.3 / $1.2
N/A
45 t/s
N/A
2.53s
262K
200K
Pick MiMo-V2-Omni if you want the stronger benchmark profile. MiniMax M2.7 only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
MiMo-V2-Omni is clearly ahead on the provisional aggregate, 84 to 53. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
MiMo-V2-Omni's sharpest advantage is in coding, where it averages 74.8 against 53.7.
MiMo-V2-Omni is the reasoning model in the pair, while MiniMax M2.7 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. MiMo-V2-Omni gives you the larger context window at 262K, compared with 200K for MiniMax M2.7.
MiMo-V2-Omni is ahead on BenchLM's provisional leaderboard, 84 to 53.
MiMo-V2-Omni has the edge for coding in this comparison, averaging 74.8 versus 53.7. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
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