Multimodal AI
Definition
AI models that can process multiple types of input, text, images, audio, video.
Why It Matters
A text-only model can describe an image only if someone first writes a caption. Multimodal models read pixels and text together in the same context, so "what does this chart show?" or "compare these two photos" becomes a single call. Same model family, more input channels.
Key Points
- Vision encoding pipeline: image → fixed-size patches → vision transformer → projected into the LLM's token embedding space.
- CLIP (2021) was the first model trained on 400M image-text pairs to align visual and language representations, still used as a vision encoder in many multimodal LLMs.
- Audio modality: raw waveform → mel spectrogram → audio transformer → token representation. Whisper uses this path for transcription; full multimodal LLMs extend it to understanding.
- Video: typically 1–2 frames per second sampled; each frame is tokenised as an image. A 60-second video clip is ~15,000 LLM tokens at standard patch sizes.
- GPT-4o, Claude 3.5 Sonnet, Gemini 1.5, and Qwen-VL are the leading multimodal models as of 2025, all natively accepting image + text in one context.
Example
GPT-4o, Claude 3.5 Sonnet, and Qwen 2.5 VL are multimodal, paste an image into chat and the model can answer questions about it without a separate vision API. Multimodal also covers audio input (Whisper-style models read raw waveforms).
Common Misconception
Multimodal input does not mean the model reasons about all modalities equally well. Text typically remains the highest-quality modality for most LLMs. Image understanding, especially spatial reasoning, counting objects, and reading fine print, is often noticeably weaker than text reasoning in the same model.
Related Terms
- Computer VisionAI that can understand and analyze images and video content.
- LLM (Large Language Model)A neural network trained on massive text datasets that can generate, understand and manipulate human language. Examples: GPT-4, Qwen, Claude.
- TransformerThe neural network architecture behind modern AI models. Introduced in the 2017 paper "Attention Is All You Need."
Multimodal AI on Rewind.ai
Image upload in chat works against any multimodal model in the picker. For audio, Rewind.ai's transcribe tool runs Whisper and routes the resulting text to whichever LLM you've picked.
Explore the ToolsQuick Facts
| Term | Multimodal AI |
| Related | Computer Vision, LLM (Large Language Model), Transformer |