Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-4.1 mini
45
MiniMax M2.7
62
Pick MiniMax M2.7 if you want the stronger benchmark profile. GPT-4.1 mini only becomes the better choice if you need the larger 1M context window.
Coding
+30.1 difference
GPT-4.1 mini
MiniMax M2.7
$0.4 / $1.6
$0.3 / $1.2
80 t/s
45 t/s
0.76s
2.53s
1M
200K
Pick MiniMax M2.7 if you want the stronger benchmark profile. GPT-4.1 mini only becomes the better choice if you need the larger 1M context window.
MiniMax M2.7 is clearly ahead on the provisional aggregate, 62 to 45. 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 23.6.
GPT-4.1 mini is also the more expensive model on tokens at $0.40 input / $1.60 output per 1M tokens, versus $0.30 input / $1.20 output per 1M tokens for MiniMax M2.7. GPT-4.1 mini gives you the larger context window at 1M, compared with 200K for MiniMax M2.7.
MiniMax M2.7 is ahead on BenchLM's provisional leaderboard, 62 to 45.
MiniMax M2.7 has the edge for coding in this comparison, averaging 53.7 versus 23.6. GPT-4.1 mini stays close enough that the answer can still flip depending on your workload.
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