MiniMax M3 百萬token上下文以5%算力成本擊敗GPT-5.5
minimax發布了m3，這是一個擁有100萬token上下文和稀疏注意力機制的開放權重模型，可將計算量降低95%。它在編碼基準測試中擊敗了gpt-5.5，這標誌著隨著開放模型匹敵專有能力，專有護城河正在消退。
chinese ai company minimax launched m3, an open-weight model combining native multimodality, a 1-million-token context, and coding performance competitive with proprietary leaders like gpt-5.5 and opus 4.7. the model uses 'minimax sparse attention' to cut compute costs by 95% and boost processing speeds, allowing it to achieve 83.5 points on browsecomp and 59% on swe-bench pro. internal tests showed m3 performing autonomous tasks such as reproducing research papers and optimizing nvidia gpu kernels for 24 hours without intervention. this development signals a significant shift in the ai landscape, as open models begin to rival proprietary systems in complex reasoning and long-context tasks.