Unlimited, because it runs on your machine
Setting up a free local app that runs open video, image and audio models on your own GPU
One app, installed with a click, running open video, image and audio models locally. The trade is explicit: you supply the GPU and the patience — several minutes per clip on a modest card — and in exchange there is no subscription and no generation limit, forever. The hardware check comes first, because this is the one setup where the answer might genuinely be “not on your machine”.
Everything runs on your own hardware, which is the entire point: no subscription, no credits, no per-generation cost, and no cap on how much you make. The cost moves instead to time and electricity. On a modest card a single short clip takes several minutes — so the workflow is to queue several and walk away, not to sit watching a progress bar.
Check your machine first
This is the step people skip and then waste an hour on. Hardware decides whether the rest of the guide applies to you at all.
Install the one-click installer
Pinokio exists to install awkward AI tooling without a terminal. It is the layer that makes the rest of this a click rather than a dependency fight.
Download it
Pick the Windows or Linux build and install it like any normal application.
Get past the safety warning
Windows will likely flag an unrecognised publisher. Choose to run it anyway — expected for a small independent tool, though it is your call to make knowingly.
Point it at your roomiest drive
First-time setup asks where to store files. Choose the drive with the most space free: this is where tens of gigabytes of models will land.
Install the app inside it
Open the discover page and search for it
The app browser lists community install scripts alongside official ones.
Pick the right script, not the default listing
The maintained community installer is the one to use — the project’s own documentation recommends it over the default entry. See the note below about which variant you need.
Download, then install, then wait
It sets up everything automatically and takes a while. Let it finish rather than intervening.
Start it and open the guides tab first
The app opens in your browser. Its built-in guides recommend which models suit your specific GPU — worth two minutes before you download a model that will not fit.
The guide sends AMD users to a separate installer variant and tells Mac users this is not for them yet. The community installer it recommends, however, describes itself as a unified installer covering NVIDIA, AMD and Apple silicon, and names specific supported AMD cards. That suggests the variants may have been merged since the guide was written. Check the installer’s own description before hunting for a separate AMD script — and if you are on a Mac, it may be worth a look rather than an automatic no.
Pick the model for the job
All of these live in one dropdown. The first time you select a model it downloads automatically — a one-time wait per model, not per generation.
Your first generation
Select a video model and leave the defaults alone
Around 480p and five seconds. Resist raising either until you know how long your card takes at the baseline.
Add an image if you have one, then describe the motion
Prompts here are about camera and atmosphere rather than subject — a slow push-in, the quality of the light, what moves in the scene, what it sounds like.
Generate, then go and do something else
Several minutes per clip on a 6-8 GB card is normal, not a fault. There is a built-in queue: stack up several and come back.
The software is genuinely free and open source. Sites that charge for access to it, or for an “installer”, are not affiliated with it. Stick to the project’s own repository and its official site, and get the installer through the app browser rather than from a search result. The project’s community chat is the place to go when something breaks — it is active, and it is free too.
The fallbacks
The hardware requirements, install sequence and model-selection guidance follow the source guide. Of the projects it points to, the community installer script and the alternative desktop launcher were both confirmed on GitHub on 16 September 2026, as was the one-click installer’s own site. The project’s canonical repository did not surface through the search index available here, though an ecosystem of forks and companion projects around it clearly exists — so treat the repository link as the guide gives it and verify it yourself before installing. Specific model names and version numbers are deliberately described by role rather than pinned, since they turn over quickly and the built-in guides recommend the right one for your card anyway.