OpenAI’s current model documentation shows modern models accepting text and image inputs, while other systems also handle live audio or video.
How does a multimodal LLM process different inputs?
Each input type passes through an encoder or tokenizer that converts it into representations the model can combine. The model reasons over a shared sequence without making every input type equally reliable. Tokenization and context limits still determine how much material fits.
When is a multimodal model useful?
Use one when the task genuinely depends on mixed evidence, such as reading charts in a report, inspecting a user interface, or answering a spoken request. A vision-language model is the focused choice for images and text. An audio language model specializes in speech and sound, while Document AI turns document content into structured information. Computer use and voice agents also need controls suited to their input channel, because screenshots and audio can contain hidden instructions or sensitive information.