MiniMax
Product information, use cases, and access for MiniMax.
Pricing information
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What is MiniMax?
MiniMax is a multimodal AI assistant for personal work, learning, and creative activity. It can answer search-oriented questions, recognize images, support voice conversations, help with writing, and analyze documents. It also covers translation, programming, office work, study, and content creation in one assistant experience.
The product supports collaboration between multiple AI agents for more complex requests. Students, professionals, independent workers, and creators can start with a natural-language instruction and continue refining the result through conversation. This creates a connected workflow from understanding source material to producing useful content.
Key features of MiniMax
Multimodal Understanding
MiniMax supports interaction involving text, images, and voice, allowing users to choose a format that fits the task. Image recognition is useful for visual material, voice conversation supports continuous communication, and text remains suitable for clearly stating questions and requirements.
Search Q&A and Document Analysis
The product provides search-oriented answers and can analyze document content. It is useful for locating information in source material, understanding longer text, and organizing key points. Users can continue asking about the same material, keeping information retrieval and follow-up understanding in one conversation.
Writing and Coding Assistance
MiniMax supports creative writing and programming-related tasks through natural-language instructions. Users can describe a content goal or a coding requirement, then use the assistant to draft text, develop an idea, generate code snippets, or clarify a development problem. This covers both expressive and technical work.
Multi-Agent Collaboration
The product supports MCP-based collaboration among multiple AI agents. Different agents can contribute to information understanding, content organization, or task progress within a complex request. This is useful for work that requires coordinated handling rather than a single isolated answer.