Workaround for video analysis + question about getting native video upload access

ChatGPT Use cases and examples
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Hi everyone,

I wanted to share a small practical workaround and also ask a question about native video upload access.

Practical workaround (not a bug)

If video upload is not available in the UI, extracting key frames from a video (JPEG/PNG) and sharing them as images still allows the model to understand the context quite well.

This works reasonably well for:

  • understanding sequences of actions

  • short-form ads / Reels analysis

  • estimating scope of work from visual context

It’s obviously not a replacement for real video upload, but it’s a useful temporary solution.

Why native video upload matters (real business use case)

I run two small businesses:

  • a construction company

  • a removals / transport company

Clients very often send videos, not photos:

  • walkthroughs of rooms, houses, gardens

  • videos showing damage or required work

  • videos of items that need to be transported

Being able to upload those videos directly and let ChatGPT:

  • analyze the scene

  • break down tasks

  • help with rough estimation or scope

would significantly reduce back-and-forth and speed up responses to clients.

Question

Is there any recommended way to:

  • request access to native video upload, or

  • signal that this capability would be used for real business workflows (not just experimentation)?

I understand rollout is gradual — just trying to understand the correct path or best practice.

Thanks, and hope the workaround helps someone else in the meantime.

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I’ve experienced similar issues and built a similar workaround, taking video and creating jpeg “filmstrips” that sample every N frames. But ultimately it’s a poor substitute for native video support. This is why I ended up changing my entire stack over to Gemini 3, which does support native video uploads in the API. When OpenAI finally catches up I’ll consider switching back.

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How do you do this properly? I’ve used cv2 with sharpest frame detection out of 3 time spots (25% 50% 100% of the video length) in the video without much success.