MiniMax-M3 is a native multimodal model with 1M context. It has 428B parameters and 23B activated parameters.
Highlights: - Native Multimodality: M3 undergoes mixed-modality training from the very first step, enabling deeper semantic fusion across text, image, and video. - Context Scaling via Sparse Attention: M3 introduces MiniMax Sparse Attention (MSA) to improve long context efficiency. M3 delivers 9× prefill and 15× decode speedups compared to M2 at 1M context, reducing per-token compute to 1/20. - Coding & Cowork Capability: M3 achieves frontier-level performance across long-horizon agentic benchmarks, excelling in both coding and cowork.
M3 is powered by **MiniMax Sparse Attention (MSA)**, a high-performance sparse attention operator designed for million-token contexts. Compared with GQA, MSA dramatically reduces the attention compute and memory footprint while preserving model q…
minimax/minimax-m3-1-flashСемейство: minimaxКонтекст (макс.): 1,05 млн токеновВвод: текст, изображения, видео; вывод: текстВозможности: рассуждение, инструменты, структурированный вывод, вложенияПоставщики: Eden AI, Kilo Gateway, LLM Gateway, Merge Gateway, NanoGPT, Novita AI и ещё 3
Источник каталога: https://models.dev/api.json. Получено: 01.11.2026 00:22 UTC. Цены и лимиты — данные источника; перед использованием проверяйте условия поставщика.