Head-to-head comparison across 2benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
MAI-Thinking-1
65
MiniMax M3
76
Verified leaderboard positions: MAI-Thinking-1 #23 · MiniMax M3 #13
Pick MiniMax M3 if you want the stronger benchmark profile. MAI-Thinking-1 only becomes the better choice if coding is the priority or you want the stronger reasoning-first profile.
Agentic
+25.9 difference
Coding
+4.0 difference
MAI-Thinking-1
MiniMax M3
N/A
$0.3 / $1.2
N/A
N/A
N/A
N/A
256K
1M
Pick MiniMax M3 if you want the stronger benchmark profile. MAI-Thinking-1 only becomes the better choice if coding is the priority or you want the stronger reasoning-first profile.
MiniMax M3 is clearly ahead on the provisional aggregate, 76 to 65. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
MiniMax M3's sharpest advantage is in agentic, where it averages 71.9 against 46. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 46% to 66%. MAI-Thinking-1 does hit back in coding, so the answer changes if that is the part of the workload you care about most.
MAI-Thinking-1 is the reasoning model in the pair, while MiniMax M3 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 M3 gives you the larger context window at 1M, compared with 256K for MAI-Thinking-1.
MiniMax M3 is ahead on BenchLM's provisional leaderboard, 76 to 65. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 46% and 66%.
MAI-Thinking-1 has the edge for coding in this comparison, averaging 71 versus 67. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
MiniMax M3 has the edge for agentic tasks in this comparison, averaging 71.9 versus 46. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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