Multimodal AI Models 2026: Vision, Audio, and Beyond
What Is Multimodal AI?
Multimodal models can process multiple types of input:
- Text + images
- Text + audio
- Text + video
Current Models
GPT-4V (Vision)
- Strength: Best overall
- Limitations: No audio/video
- Best for: Image analysis, document OCR
Claude Vision
- Strength: Best for code from images
- Limitations: Slower
- Best for: Screenshot analysis, UI debugging
Gemini 2.0
- Strength: Native multimodal (text, image, audio, video)
- Limitations: Less proven
- Best for: Complex multimodal tasks
Use Cases
Document Processing
Extract text from images, PDFs, screenshots.
Code Understanding
Analyze architecture diagrams, flowcharts.
Image Analysis
Debug UI issues, analyze plots.
Audio Transcription
Transcribe and analyze audio.
Capabilities Comparison
| Task | GPT-4V | Claude | Gemini |
|---|---|---|---|
| OCR | Excellent | Good | Excellent |
| Screenshots | Good | Excellent | Good |
| Diagrams | Good | Good | Excellent |
| Video | ✗ | ✗ | ✓ |
When to Use Multimodal
- Processing uploaded images
- Screenshot analysis
- Document digitization
- Visual debugging
Cost
Multimodal is 2-3x more expensive than text-only. Use only when needed.