Complete Guide to Multimodal AI Models: Text, Image, Video in One

For years, AI was limited to text.

Then came image generation (DALL-E), image understanding (GPT-4V), and now video understanding. But most people still treat these as separate tools.

The real power is multimodal AI: understanding text, images, and video in the same request, in the same context.

This changes everything about what's possible.

This guide explains what multimodal AI is, why it matters, which models lead the space, and how to use it in your workflow.

What is Multimodal AI?

Simple definition: AI that understands multiple types of input (text, images, video, audio) simultaneously.

Before (limited):

Text model ← understands only text
Image model ← understands only images
You have to switch between tools

Now (multimodal):

One model ← understands text, images, video, audio
Seamless workflow, shared context

Example: Processing a Product Page

Without multimodal (old way):

1. Read text description with GPT-4: 5 seconds
2. Analyze product images with Claude Vision: 5 seconds
3. Manually combine insights: 10 minutes
4. Decide which to use: frustration

With multimodal (new way):

1. Send text + images to Gemini: 3 seconds
2. Model understands them together: automatic
3. Get unified analysis: 30 seconds total

Types of Multimodal AI

Type 1: Text-to-Image

Input: Text prompt Output: Images

Examples: DALL-E 3, Midjourney, Stable Diffusion XL Use case: Generate images from descriptions

Type 2: Image-to-Text

Input: Image(s) Output: Text description, analysis, answers

Examples: GPT-4V, Claude Vision, Gemini Vision Use case: Understand images, extract information

Type 3: Video-to-Text

Input: Video Output: Transcript, description, summary, answers

Examples: Gemini (video), Claude (coming soon) Use case: Analyze video content

Type 4: Text + Image → Text (True Multimodal)

Input: Text question + Images Output: Text answer combining both

Examples: GPT-4 with Vision, Claude 3 Opus, Gemini Use case: Analyze images in context of questions

Type 5: Text + Image + Video → Text (Full Multimodal)

Input: Text + Images + Video clips Output: Unified analysis

Examples: Gemini (latest version) Use case: Comprehensive analysis combining all media

Best Multimodal Models in 2025

1. Gemini (Google) - Best Overall Multimodal

What it does: Understand text, images, AND video simultaneously.

Key strength: Video understanding (1M token context lets you load entire videos)

Modalities:

✅ Text input/output
✅ Image input
✅ Video input (major advantage)
✅ Audio input
✅ Code understanding
✅ Web access

Performance:

Text: Excellent
Vision: Very good (better than most)
Video: Best in class
Speed: Fast

Pricing:

Free tier: Limited
Pro: $19.99/month
Enterprise: Custom

Use cases:

Analyzing competitor videos
Processing multiple media types
Understanding complex visual content
Content creators (video analysis)

Example:

Input:
- Question: "What are the key features demonstrated in this product video?"
- Video file: product_demo.mp4
- Additional context: "We're comparing against competitors X and Y"

Output: Detailed analysis of features, how they compare, recommendations

2. Claude 3 Opus (Anthropic) - Best for Analysis

What it does: Understand text and images with exceptional reasoning.

Key strength: Deep analysis of complex images and documents.

Modalities:

✅ Text input/output
✅ Image input (excellent quality)
❌ Video input (not yet, coming soon)
❌ Audio input
✅ Code understanding
❌ Web access

Performance:

Text: Excellent (best reasoning)
Vision: Excellent (understand complex images)
Speed: Good (not as fast as Gemini)

Pricing:

API: $3 input / $15 output per 1M tokens
Claude.ai: $20/month Pro

Use cases:

Analyzing documents with images/diagrams
Complex reasoning about visual content
Understanding charts, graphs, layouts
Research (papers with diagrams/data)

Example:

Input:
- PDF scan of a legal contract (text + images)
- Question: "Identify all liability clauses and explain in simple terms"

Output:
Structured analysis of each clause with explanations
(Claude reads both text and images together)

3. GPT-4 with Vision (OpenAI) - Most Popular

What it does: Text input + image input → text output with excellent reasoning.

Key strength: Most widely adopted, excellent at understanding images in context.

Modalities:

✅ Text input/output
✅ Image input
❌ Video input
❌ Audio input
✅ Code understanding
❌ Web access

Performance:

Text: Excellent
Vision: Very good (good understanding, sometimes makes mistakes)
Speed: Fast

Pricing:

API: $3 per 1M input / $15 per 1M output tokens
ChatGPT Plus: $20/month

Use cases:

General image analysis
Code review (reading screenshots)
Diagram understanding
UI/UX feedback (website screenshots)

Example:

Input:
- Question: "Review this website screenshot for UX issues"
- Image: website_screenshot.png

Output:
Detailed UX analysis with specific recommendations

4. Gemini with Video - Best for Creators

What it does: Process entire videos, extract insights, summarize content.

Key strength: Video understanding (unique advantage in late 2025)

Modalities:

✅ Text
✅ Image
✅ Video (unique)
✅ Audio
✅ Code
✅ Web access

Performance:

Video understanding: Best available
Context: 1M tokens (load entire movies)
Speed: Good

Pricing: $19.99/month Gemini Advanced

Use cases:

Content creators analyzing videos
Research teams processing video data
Competitive analysis (competitor videos)
Video editing and summarization

Example:

Input:
- Question: "Summarize this 2-hour course video and extract key learning points"
- Video: course_video.mp4

Output:
- Summary of each section
- Key takeaways
- Quiz questions
- Time stamps for important topics

Comparison Table

Model	Text	Image	Video	Audio	Speed	Cost	Best For
Gemini	⭐⭐⭐⭐	⭐⭐⭐⭐	⭐⭐⭐⭐⭐	⭐⭐⭐	Fast	$20/mo	Overall multimodal
Claude 3 Opus	⭐⭐⭐⭐⭐	⭐⭐⭐⭐⭐	❌	❌	Good	API	Analysis
GPT-4V	⭐⭐⭐⭐	⭐⭐⭐⭐	❌	❌	Fast	API	General use
Grok	⭐⭐⭐	⭐⭐⭐⭐	❌	❌	Fast	API	Fast inference

Real-World Use Cases

Use Case 1: Content Creator

Goal: Create YouTube scripts from competitor videos

Workflow:

Upload 3 competitor videos to Gemini
Ask: "Extract the structure, tone, and key points from each video"
Get: Detailed analysis of each
Use: As template for your own script

Time saved: 3 hours → 15 minutes

Use Case 2: Researcher

Goal: Extract data from research papers with charts

Workflow:

Upload PDF (text + images/charts)
Ask: "Extract all numerical data and explain what each chart shows"
Get: Structured data + interpretations
Use: For analysis

Time saved: 2 hours → 10 minutes

Use Case 3: Developer

Goal: Debug UI issues

Workflow:

Take screenshot of broken UI
Ask Claude/GPT: "What's wrong with this UI? How would you fix it?"
Get: Specific issues and solutions
Implement fixes

Time saved: 30 minutes → 5 minutes

Use Case 4: Business Analyst

Goal: Analyze competitor website + pitch deck

Workflow:

Screenshot competitor website + upload their pitch deck PDF
Ask: "What are their key differentiators? How do they position themselves?"
Get: Analysis combining both sources
Use: For positioning your product

Time saved: 1 hour → 10 minutes

How to Use Multimodal Models

With Gemini:

1. Go to gemini.google.com
2. Click the attachment icon
3. Upload image, PDF, or video
4. Ask your question
5. Gemini analyzes everything together

With GPT-4 Vision:

1. ChatGPT Plus or API
2. In conversation, click attachment
3. Upload image
4. Ask your question
5. Include {image} in your prompt

With Claude:

1. Claude.ai or API
2. Upload image using attachment button
3. Ask your question
4. Claude analyzes in context

Programmatic Access (API):

import anthropic
 
client = anthropic.Anthropic()
 
message = client.messages.create(
    model="claude-3-opus-20240229",
    max_tokens=1024,
    messages=[
        {
            "role": "user",
            "content": [
                {
                    "type": "image",
                    "source": {
                        "type": "url",
                        "url": "https://example.com/image.png",
                    },
                },
                {
                    "type": "text",
                    "text": "What is in this image?"
                }
            ],
        }
    ],
)
 
print(message.content[0].text)

Best Practices for Multimodal AI

1. Be Specific About What You Want

Bad: "Analyze this image" Good: "Analyze this product image. Evaluate: design, colors, typography, layout. What improvements would you suggest?"

2. Provide Context

Bad: Upload image and ask "What do you see?" Good: "I'm redesigning my website. This is my competitor's hero section. How does it compare to common best practices? What would you improve?"

3. Use Multiple Images Together

Bad: Upload one image at a time Good: Upload 3 competitor images + your own. "Compare these four websites. What works? What's missing?"

4. For Video: Provide Questions

Bad: "Summarize this video" Good: "Extract these from the video: key claims, evidence provided, expert credentials, any red flags"

First: "Analyze this screenshot for UX issues" Follow-up: "Suggest specific fixes for each issue you mentioned. Include code examples if applicable"

The Future of Multimodal AI

Coming in 2025-2026:

✅ Video understanding becomes standard (Gemini, coming to Claude)
✅ Real-time multimodal (live video analysis)
✅ 3D object understanding
✅ Audio+text combined (better voice transcription + understanding)
✅ Document processing (PDF, word, presentations natively)
⚠️ Still missing: True understanding (vs pattern matching)

Not coming anytime soon:

Understanding context across domains
Common sense reasoning
Understanding causality
True reasoning (just pattern matching, very good)

Why Dotlane's Multimodal Approach Matters

Instead of using 4 different tools:

GPT-4V for images
Gemini for video
Claude for analysis
Grok for speed

Dotlane's advantage: Test all models on the same images, compare results, choose best.

Example:

Upload image → See analysis from:
- GPT-4V
- Claude Vision
- Gemini
- Grok

Compare quality, speed, cost → Choose best for your task

The Bottom Line

Multimodal AI is transformative. It's not just about understanding images—it's about understanding images in context alongside text, with reasoning and analysis.

This changes what's possible:

Creators: Analyze competitor content in minutes
Researchers: Process documents with diagrams automatically
Developers: Debug visual issues with AI
Business analysts: Understand landscapes combining multiple sources

Start today: Upload an image to Gemini or Claude, ask a detailed question, see what becomes possible.

The next productivity leap isn't a new tool. It's using multimodal AI you probably already have access to.