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MiniMax M3

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Processes long multimodal sequences across text, images, and video.

MiniMaxMultimodalClosed
Model page Updated 2026-06-14

About MiniMax M3

MiniMax M3 combines separate encoders for text, still images, and video frames into a single transformer backbone. Its 1,048,576-token context supports ingestion of hour-long video transcripts together with reference images and lengthy documents without segmentation. The architecture remains proprietary and is accessed only through MiniMax APIs.

Strengths include coherent reasoning over long multimodal timelines and the ability to reference visual details across distant parts of an input. Typical usage covers video summarization, long-form document analysis with illustrations, and interactive media assistants that maintain context across many turns.

Capabilities

Long-context reasoning
Multimodal input processing
Image understanding
Video comprehension
Cross-modal analysis
Text generation

Best for

Extended video comprehension projects

MiniMax M3 processes full-length videos within its 1M-token context to deliver cross-modal summaries that integrate visual scenes with spoken or textual elements.

Long-document image analysis

The model handles lengthy reports or research papers paired with multiple images, performing cross-modal analysis to extract consistent insights across modalities.

Multimodal reasoning over archives

It supports long-context reasoning tasks that combine text generation with image and video inputs for unified answers spanning thousands of pages or hours of content.

Strengths & limitations

Strengths

  • +Very large 1M-token context window
  • +Native text, image, and video support
  • +Unified multimodal handling

Limitations

  • Large context increases compute cost
  • May trade speed for multimodal breadth
  • Less specialized than single-modality models

Where to access MiniMax M3

Frequently asked questions

MiniMax M3 provides a context window of 1,048,576 tokens.

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