What is Multimodal?

An AI model that handles more than one type of input or output — e.g. text plus images, audio or video.

A multimodal model works with more than one type of data, such as text, images, audio, or video, either as input, output, or both. Instead of separate systems for each format, the model maps different data types into a shared internal representation, so it can describe a photo, answer questions about a chart, or transcribe and summarize a voice note in one step. Most flagship models today (GPT, Claude, Gemini) accept images alongside text, and some handle audio and video natively. Practical nuance: "multimodal" varies a lot by product. Some models only read images (input), some also generate them (output), and quality differs per modality. Check exactly which formats a tool accepts and produces, and whether media inputs cost more tokens, before you commit.

Example

You upload a screenshot of a broken invoice layout to a chatbot and ask what is wrong. The model reads the image, spots the misaligned totals column, and suggests a fix, no manual description needed.

Why it matters

If your workflow involves screenshots, PDFs with charts, audio, or video, a genuinely multimodal model saves you from converting everything to text first. Verify which modalities are supported in each direction. Browse the AI tools directory or the model leaderboard to put it into practice.