Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
MiniMax M2.7 is clearly ahead on the aggregate, 57 to 51. 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 56.2 against 42.5. The single biggest benchmark swing on the page is SWE-bench Pro, 56.2% to 42%.
o4-mini (high) 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.
Pick MiniMax M2.7 if you want the stronger benchmark profile. o4-mini (high) only becomes the better choice if you want the stronger reasoning-first profile.
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
MiniMax M2.7
56.2
o4-mini (high)
42.5
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
Benchmark data for this category is coming soon.
Benchmark data for this category is coming soon.
Comparable scores for this category are coming soon. One or both models do not have sourced results here yet.
MiniMax M2.7 is ahead overall, 57 to 51. The biggest single separator in this matchup is SWE-bench Pro, where the scores are 56.2% and 42%.
MiniMax M2.7 has the edge for coding in this comparison, averaging 56.2 versus 42.5. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
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