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Ami StudioOleksii Zahlukha

Video toolingLocal video generation on my own GPU

Local video generation on my own GPU

Video generated on my own graphics card instead of a paid cloud service — an experiment costs a second, not an invoice.

Actually used by the content factory, not just benchmarked once.

What it is

Neural video generation is almost always bought from a cloud service by the piece. That works while you already know what you want. But in real work the first hundred attempts are rubbish: you are still tuning the wording, the length, the style, the camera move. Paid by the piece, that tuning turns into a budget line, and people start economising in the one place where they should not.

Here the models run on my own card, and an attempt costs time, and time only. A hundred failed runs on a rented service is an invoice; on your own card it is an evening. As a side effect, neither the source material nor the result goes anywhere, which matters when somebody else’s footage is in the frame.

Specifications: local diffusion models, a Python harness, an RTX 5060 graphics card. The limit is honest too and comes down to the card’s memory: clip length and resolution here are lower than a paid service gives. This is a working tool for tuning and drafts, not a replacement for the cloud on a final render. It was used by the Content Factory in real work.

Nearby work

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