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

**URL:** <https://community.openai.com/t/workaround-for-video-analysis-question-about-getting-native-video-upload-access/1369186>\
**Category:** Use cases and examples\
**Tags:** video, business-content, feature-request, chatgpt-business, workflow\
**Created:** [December 13, 2025, 12:59pm UTC](https://community.openai.com/t/workaround-for-video-analysis-question-about-getting-native-video-upload-access/1369186 "2025-12-13T12:59:48Z")\
**Posts on this page:** 3\
**Page:** 1

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**Author:** ![gichka.sergejj](https://sea2.discourse-cdn.com/openai1/user_avatar/community.openai.com/gichka.sergejj/32/707160_2.png) [@gichka.sergejj](https://community.openai.com/u/gichka.sergejj)\
**Post date:** [December 13, 2025, 12:59pm UTC](https://community.openai.com/t/workaround-for-video-analysis-question-about-getting-native-video-upload-access/1369186/1 "2025-12-13T12:59:48Z")

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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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**Author:** ![daniel.gelernter](https://sea2.discourse-cdn.com/openai1/user_avatar/community.openai.com/daniel.gelernter/32/353581_2.png) [@daniel.gelernter](https://community.openai.com/u/daniel.gelernter)\
**Post date:** [January 6, 2026, 9:44pm UTC](https://community.openai.com/t/workaround-for-video-analysis-question-about-getting-native-video-upload-access/1369186/2 "2026-01-06T21:44:57Z")

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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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**Author:** ![MissingHistory](https://avatars.discourse-cdn.com/v4/letter/m/f9ae1b/32.png) [@MissingHistory](https://community.openai.com/u/MissingHistory)\
**Post date:** [January 20, 2026, 12:49pm UTC](https://community.openai.com/t/workaround-for-video-analysis-question-about-getting-native-video-upload-access/1369186/3 "2026-01-20T12:49:41Z")

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> [@gichka.sergejj](#):
>
> extracting key frames from a video

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.