MiniMax M3의 1M 토큰 컨텍스트, 5% 연산 비용으로 GPT-5.5 제친
MiniMax가 M3를 공개했습니다. 100만 토큰 컨텍스트와 연산량을 95% 줄이는 희소 어텐션을 갖춘 오픈 웨이트 모델입니다. 코딩 벤치마크에서 GPT-5.5를 능가하며, 오픈 모델이 독점 모델의 성능에 도달하면서 독점 해자가 침식되고 있음을 시사합니다.
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.