Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Mellum2-12B-A2.5B-Thinking
59
MiniMax M2.7
54
Pick Mellum2-12B-A2.5B-Thinking if you want the stronger benchmark profile. MiniMax M2.7 only becomes the better choice if you need the larger 200K context window or you would rather avoid the extra latency and token burn of a reasoning model.
Coding
+16.2 difference
Mellum2-12B-A2.5B-Thinking
MiniMax M2.7
N/A
$0.3 / $1.2
N/A
45 t/s
N/A
2.53s
128K
200K
Pick Mellum2-12B-A2.5B-Thinking if you want the stronger benchmark profile. MiniMax M2.7 only becomes the better choice if you need the larger 200K context window or you would rather avoid the extra latency and token burn of a reasoning model.
Mellum2-12B-A2.5B-Thinking is clearly ahead on the provisional aggregate, 59 to 54. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Mellum2-12B-A2.5B-Thinking's sharpest advantage is in coding, where it averages 69.9 against 53.7.
Mellum2-12B-A2.5B-Thinking 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 gives you the larger context window at 200K, compared with 128K for Mellum2-12B-A2.5B-Thinking.
Mellum2-12B-A2.5B-Thinking is ahead on BenchLM's provisional leaderboard, 59 to 54.
Mellum2-12B-A2.5B-Thinking has the edge for coding in this comparison, averaging 69.9 versus 53.7. MiniMax M2.7 stays close enough that the answer can still flip depending on your workload.
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