Why AI Agents Need Million-Token Context — Thomas Wolf & Olive Song, MiniMax
Sep 4, 2026 · 20:48
MiniMax's M3 pairs a functional one-million-token context window with coding and multimodal abilities in a 400-billion-parameter, 20-billion-activated model, explain Olive Song, RL Lead at MiniMax, and Thomas Wolf, co-founder of Hugging Face. Song says short context fails when agents handle multi-round tool responses; MiniMax Sparse Attention — an index branch selecting what matters plus a sparse branch computing on selected blocks — was designed by an intern. She argues multimodal training from the very first step beats post-hoc adapters that harm text performance and risk collapse; interleaved data and reward modeling solved this. Its apps reach over 300 million people in 200 countries; anyone can propose projects, and community feedback and internal agent harnesses now drive M3.1.
