MiniMax M2-her

MiniMax M2-her is a dialogue-first model purpose-built for role-playing and immersive multi-turn conversations. Developed from three years of role-play optimization, it excels at intuitive preference alignment (reading between the lines to adapt to user style), dynamic story progression (driving narrative forward with vivid prose), and high-fidelity world experience (maintaining strict coherence with established lore and character voice). Supports rich role settings including system roles, user personas, conversation groups, and example dialogue learning. With a 200K context window and 2K max output, it prioritizes deep emotional connection and long-horizon character consistency over raw output length.