Side-by-side benchmark comparison across knowledge, coding, math, and reasoning.
MiniMax M2.5 is clearly ahead on the aggregate, 66 to 43. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
MiniMax M2.5 is also the more expensive model on tokens at $0.30 input / $1.20 output per 1M tokens, versus $0.15 input / $0.60 output per 1M tokens for GPT-4o mini. That is roughly 2.0x on output cost alone.
Pick MiniMax M2.5 if you want the stronger benchmark profile. GPT-4o mini only becomes the better choice if coding is the priority or you want the cheaper token bill.
MiniMax M2.5
61
GPT-4o mini
82
MiniMax M2.5
48.3
GPT-4o mini
87.2
MiniMax M2.5
84
GPT-4o mini
87
MiniMax M2.5 is ahead overall, 66 to 43. The biggest single separator in this matchup is HumanEval, where the scores are 65 and 87.2.
GPT-4o mini has the edge for knowledge tasks in this comparison, averaging 82 versus 61. Inside this category, MMLU is the benchmark that creates the most daylight between them.
GPT-4o mini has the edge for coding in this comparison, averaging 87.2 versus 48.3. Inside this category, HumanEval is the benchmark that creates the most daylight between them.
GPT-4o mini has the edge for multilingual tasks in this comparison, averaging 87 versus 84. Inside this category, MGSM is the benchmark that creates the most daylight between them.
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