---
title: "Processing Video Files with Vercel AI SDK v7 Multimodal Support"
description: "Language models can finally see more than just text. I tested the new multimodal capabilities in Vercel AI SDK v7 to analyze raw video files."
image: "https://foundrysoft.co/api/og?type=article&title=Processing+Video+Files+with+Vercel+AI+SDK+v7+Multimodal+Support&cat=AI+Engineering&rt=7+min+read&au=Varun+Raj+Manoharan&dt=2026-07-06"
url: "https://foundrysoft.co/blog/vercel-ai-sdk-v7-multimodal-inputs"
---

AI Engineering 2026-07-06 7 min read

# Processing Video Files with Vercel AI SDK v7 Multimodal Support

Language models can finally see more than just text. I tested the new multimodal capabilities in Vercel AI SDK v7 to analyze raw video files.

![Varun Raj Manoharan](https://foundrysoft.co/images/about/founder.webp)

Varun Raj Manoharan

Vercel AI SDK v7 Multimodal Video

We spent the last two years feeding text strings into language models. Now the models can actually see what we see. Vercel AI SDK v7 pushes hard into multimodal territory, letting you pass images, audio, and even video files directly into your prompts.

I wanted to see how well it handles moving pictures, so I built a small script to ingest a short video clip and spit out a summary.

### Dropping in the Video

You do not have to write custom chunking logic or extract frames manually anymore. The SDK abstracts the heavy lifting. You just pass the file as a part of the `messages` array.

TypeScript

Copy

```typescript
import { generateText } from 'ai';
import { google } from '@ai-sdk/google';
import fs from 'fs/promises';

async function analyzeVideo() {
  const videoBuffer = await fs.readFile('./meeting-recording.mp4');

  const { text } = await generateText({
    model: google('gemini-3-pro'),
    messages: [
      {
        role: 'user',
        content: [
          { type: 'text', text: 'Watch this video and tell me what the three main action items were.' },
          {
            type: 'file',
            data: videoBuffer,
            mimeType: 'video/mp4',
          },
        ],
      },
    ],
  });

  console.log(text);
}

analyzeVideo();
```

### The Results

I fed it a three-minute recording of a standup meeting. It chewed on it for about ten seconds and correctly pulled out the action items, even noting that one developer pointed at a specific line of code on the shared screen.

There is a catch, though. The models still struggle with temporal reasoning, understanding _when_ something happened in a ten-minute video is harder than just recognizing _what_ happened. You also have to watch your token limits. A long high-definition video will eat through your context window faster than you can blink.

If you are just summarizing short clips or pulling data from screen recordings, the v7 API makes it trivial. Just keep an eye on the billing dashboard.

#### Related reading

[Teaching an Agent Our Client Reporting Playbook with Vercel AI SDK v7 Skills

Our monthly client reports followed a 40-line prompt nobody dared touch. I moved the whole playbook into an uploaded skill using the new uploadSkill API in Vercel AI SDK v7.

Vercel AI SDK v7

](https://foundrysoft.co/blog/vercel-ai-sdk-v7-agent-skills)[Building a Realtime Voice Support Agent with Vercel AI SDK v7

Voice agents used to mean marrying one provider's WebSocket event format. I used the new experimental realtime API in Vercel AI SDK v7 to build an order-status voice agent I can move between providers.

Vercel AI SDK v7

](https://foundrysoft.co/blog/vercel-ai-sdk-v7-realtime-voice-agent)[Letting an Agent Run Shell Commands Safely with Vercel AI SDK v7 Sandboxes

I built a dependency-audit agent that runs npm commands on real projects. The new experimental sandbox support in Vercel AI SDK v7 is what made me comfortable shipping it.

Vercel AI SDK v7

](https://foundrysoft.co/blog/vercel-ai-sdk-v7-sandboxed-command-execution)

#### Next Article

[

Finding Slow Tool Calls in Vercel AI SDK v7 Telemetry

](https://foundrysoft.co/blog/vercel-ai-sdk-v7-telemetry-tracing)

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