Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
MiniMax M2.7
62
o3-mini
56
Pick MiniMax M2.7 if you want the stronger benchmark profile. o3-mini only becomes the better choice if you want the stronger reasoning-first profile.
Coding
+4.4 difference
MiniMax M2.7
o3-mini
$0.3 / $1.2
$1.1 / $4.4
45 t/s
160 t/s
2.53s
7.12s
200K
200K
Pick MiniMax M2.7 if you want the stronger benchmark profile. o3-mini only becomes the better choice if you want the stronger reasoning-first profile.
MiniMax M2.7 is clearly ahead on the provisional aggregate, 62 to 56. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
MiniMax M2.7's sharpest advantage is in coding, where it averages 53.7 against 49.3.
o3-mini is also the more expensive model on tokens at $1.10 input / $4.40 output per 1M tokens, versus $0.30 input / $1.20 output per 1M tokens for MiniMax M2.7. That is roughly 3.7x on output cost alone. o3-mini 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.
MiniMax M2.7 is ahead on BenchLM's provisional leaderboard, 62 to 56.
MiniMax M2.7 has the edge for coding in this comparison, averaging 53.7 versus 49.3. o3-mini stays close enough that the answer can still flip depending on your workload.
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