Multimodal
Multimodal
Multimodal models handle more than one data type, such as text and images.
Quick definition
Multimodal models handle more than one data type, such as text and images.
- Category: Multimodal
- Focus: cross-modal understanding
- Used in: Analyzing screenshots or images with text questions.
What it means
They can reason across modalities in a single prompt. In multimodal workflows, multimodal often shapes cross-modal understanding.
How it works
Multimodal models align text, vision, and audio signals so one system can reason across modalities.
Why it matters
Multimodal features unlock workflows across text, audio, and images.
Common use cases
- Analyzing screenshots or images with text questions.
- Transcribing speech and summarizing meetings.
- Generating voice responses from text outputs.
Example
Ask a model to describe an image and answer questions about it.
Pitfalls and tips
Noisy inputs lead to unreliable results. Provide clear images, clean audio, and explicit instructions.
In BoltAI
In BoltAI, this appears when working with audio, images, or voice.
