Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
MiniMax M1 80k is clearly ahead on the aggregate, 37 to 31. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5 nano is the reasoning model in the pair, while MiniMax M1 80k 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-5 nano gives you the larger context window at 400K, compared with 80K for MiniMax M1 80k.
Pick MiniMax M1 80k if you want the stronger benchmark profile. GPT-5 nano only becomes the better choice if mathematics is the priority or you need the larger 400K context window.
MiniMax M1 80k
31.3
GPT-5 nano
71.2
MiniMax M1 80k
37.8
GPT-5 nano
85.2
MiniMax M1 80k is ahead overall, 37 to 31. The biggest single separator in this matchup is AIME 2025, where the scores are 37 and 85.2.
GPT-5 nano has the edge for knowledge tasks in this comparison, averaging 71.2 versus 31.3. Inside this category, GPQA is the benchmark that creates the most daylight between them.
GPT-5 nano has the edge for math in this comparison, averaging 85.2 versus 37.8. Inside this category, AIME 2025 is the benchmark that creates the most daylight between them.
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