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MiniMax
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MaxProof's innovative test-time scaling enables an AI to outperform human champions in mathematical proof competitions.
MiniMax-M2 proves that massive parameter counts don't always translate to better agentic performance; strategic activation of a smaller subset can unlock frontier-level intelligence.
Reasoning beats scale: a 1.5B parameter model, READER, outperforms models 100-1000x larger in detecting AI-generated text by explicitly generating a rationale for its decision.
