Head-to-head comparison across 3benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
GPT-4.1 mini
45
MAI-Thinking-1
65
Verified leaderboard positions: GPT-4.1 mini unranked · MAI-Thinking-1 #23
Pick MAI-Thinking-1 if you want the stronger benchmark profile. GPT-4.1 mini only becomes the better choice if instruction following is the priority or you need the larger 1M context window.
Coding
+47.4 difference
Knowledge
+5.7 difference
Inst. Following
+3.5 difference
GPT-4.1 mini
MAI-Thinking-1
$0.4 / $1.6
N/A
80 t/s
N/A
0.76s
N/A
1M
256K
Pick MAI-Thinking-1 if you want the stronger benchmark profile. GPT-4.1 mini only becomes the better choice if instruction following is the priority or you need the larger 1M context window.
MAI-Thinking-1 is clearly ahead on the provisional aggregate, 65 to 45. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
MAI-Thinking-1's sharpest advantage is in coding, where it averages 71 against 23.6. The single biggest benchmark swing on the page is SWE-bench Verified, 23.6% to 73.5%. GPT-4.1 mini does hit back in instruction following, 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 GPT-4.1 mini 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. GPT-4.1 mini gives you the larger context window at 1M, compared with 256K for MAI-Thinking-1.
MAI-Thinking-1 is ahead on BenchLM's provisional leaderboard, 65 to 45. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 23.6% and 73.5%.
MAI-Thinking-1 has the edge for knowledge tasks in this comparison, averaging 69.9 versus 64.2. Inside this category, GPQA is the benchmark that creates the most daylight between them.
MAI-Thinking-1 has the edge for coding in this comparison, averaging 71 versus 23.6. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
GPT-4.1 mini has the edge for instruction following in this comparison, averaging 88.5 versus 85. MAI-Thinking-1 stays close enough that the answer can still flip depending on your workload.
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