# Multimodal AI Models: Which Can Handle Image

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# Multimodal AI Models: Which Can Handle Image, Audio, and Video?

Published in the LLMNet Hub | Last update: July 2026

The generative AI market has drastically shifted from purely text-driven models to fully multimodal systems. Modern architectures can simultaneously reason across text, images, audio, and video. This overview highlights, at a conceptual level, which well-known models support which modalities.

## Explanation of the Modalities

- Text: The foundation of Large Language Models (LLMs) for instructions, code, and synthesis.

- Image (Vision): Analyzing, generating, or editing still photography and graphic elements.

- Audio: Native processing of speech and sound (input via microphone, output via text-to-speech or direct audio generation) without requiring a transcription step.

- Video: Understanding video streams (frame-by-frame analysis) or generating moving images.

## Comparison Table of Well-Known Models

Model / Series | 
Text | 
Image | 
Audio | 
Video | 

OpenAI GPT-4o | 
Yes | 
Yes | 
Yes (Native) | 
Limited (Frames) | 

Google Gemini 1.5 Pro | 
Yes | 
Yes | 
Yes | 
Yes (Native) | 

Anthropic Claude 3.5 Sonnet | 
Yes | 
Yes | 
No | 
No | 

Meta Llama 3.2 (Vision) | 
Yes | 
Yes | 
No | 
No | 

Note: Support for audio and video varies greatly by API implementation and whether it concerns model input, output, or both. Some specifications are based on public releases and may be subject to updates.

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