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MiniMax M2.7: First 'Self-Evolving' Model Runs 100+ Autonomy Cycles, Scores 56.2% on SWE-Pro — 317 Upvotes
MiniMax M2.7, which launched March 18, is generating renewed community interest (317↑, 30cmts on r/LocalLLaMA) as practitioners discover its self-evolution capability: the model autonomously ran 100+ rounds of scaffold optimization during training, achieving 30% performance improvement without human intervention. It scores 56.22% on SWE-Pro (near Opus-level), maintains 97% skill adherence across 40+ complex skills, and costs just $0.30/$1.20 per million input/output tokens — an order of magnitude cheaper than frontier models.
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