Open Generative AI is a self-hosted desktop app that puts more than 400 AI image and video models, including Flux, Midjourney, Kling, Sora, and Veo, behind one interface. It is built by developer Anil Matcha, it is MIT licensed, and it has picked up close to 26,000 GitHub stars. Here is what it actually does, what “free” really means once you install it, and how to get it running today.
What Open Generative AI Actually Is
Most AI image and video tools lock you into one company’s models and one subscription. Open Generative AI takes the opposite approach. It is a single interface, built on Next.js and packaged as an Electron desktop app, that sits on top of over 400 models from more than a dozen providers. Instead of paying separately for Midjourney, a Kling subscription, and a Sora account, you get one workspace with all of them available side by side.
The app is organized into studios, each built for a different kind of generation.
Image Studio switches automatically between text-to-image and image-to-image depending on whether you upload a reference photo. It covers more than 70 models on each side, including Flux, Nano Banana 2, Seedream 5.0, Ideogram, GPT-4o, and Midjourney-style options.
Video Studio follows the same pattern for text-to-video and image-to-video, pulling from Kling, Sora, Veo, Wan, Seedance, and Runway among others.
Lip Sync Studio animates a portrait photo or an existing video to match an audio track, using nine dedicated models.
Cinema Studio adds proper camera language to your prompts, with presets for lens type, focal length, and aperture, so you are directing a shot instead of just describing one.
Workflow Studio lets you chain models together in a node-based builder, so the output of one generation feeds directly into the next step without you copying files around manually.
There are additional studios for audio generation, marketing creative, body swapping, and an autonomous agent mode that plans and runs generation tasks conversationally. The whole thing runs off a single shared model catalog, so a new model added to the underlying library shows up automatically across every studio that supports it.
The Catch: What Is Actually Free
Here is the part the GitHub description does not lead with. Open Generative AI is genuinely free and open source as software. The interface, the code, the ability to self-host and modify it, all of that costs nothing and carries an MIT license, which is about as permissive as licensing gets.
Generating an actual image or video is a different question. The app itself does not run Flux, Midjourney, Kling, or Sora on your computer. It sends your prompt to Muapi.ai, a third party API gateway that hosts all of those models and bills per generation. There is no subscription, and pricing is metered per call, roughly a few cents for a still image up to tens of cents for a longer video, depending on the model and resolution you pick. You buy credits up front and they get deducted as you generate.
That means most of what makes this app exciting, the access to Sora, Veo, Kling, and Midjourney in one place, still costs money. What Open Generative AI removes is the subscription lock-in and the platform walls between services, not the underlying compute cost of running frontier video models.
There is one genuine exception. The desktop app ships with two local inference options that need no API key and no ongoing cost.
sd.cpp is bundled directly into the app and runs entirely on your own hardware, with Metal acceleration on Apple Silicon and CUDA or ROCm support on Windows and Linux. It covers smaller, older-generation models like SD 1.5, SDXL, and Z-Image, all image only.
Wan2GP is a separate server you run yourself on a machine with an NVIDIA or AMD GPU. Point the desktop app at it and you get Flux Dev, Qwen Image, and video models like Wan 2.2, Hunyuan, and LTX, running completely locally with no per-generation fee.
If you want the marquee cloud models, budget for Muapi credits. If you are fine with SD 1.5 or a self-hosted Flux Dev setup, you can run this without spending anything beyond your own electricity bill.
How the Model Categories Break Down
| Category | Roughly How Many Models | Examples |
|---|---|---|
| Text-to-Image | 70+ | Flux Dev, Nano Banana 2, Seedream 5.0, Ideogram v3, Midjourney |
| Image-to-Image | 70+ | Flux Kontext, Nano Banana 2 Edit, Seededit, upscalers |
| Text-to-Video | 85+ | Kling, Sora 2, Veo 3, Wan, Seedance, Runway |
| Image-to-Video | 120+ | Kling I2V, Veo3 I2V, Runway I2V, Wan I2V |
| Lip Sync | 15 | Infinite Talk, LTX Lipsync, Sync, LatentSync |
| Audio | 15+ | Text-to-music, remix, and editing models |
That is a genuinely large catalog, and the app is set up so a reference image automatically flips a studio from text mode into image editing mode, which saves you from hunting through separate menus for each task.
How to Install It (Step by Step)
You have two ways to use Open Generative AI: the hosted browser version, or the self-hosted desktop app. The browser version needs zero setup.
- Go to muapi.ai/open-generative-ai if you want to try it in a browser with no install. Sign up for a free account and you can start generating right away using your purchased credits.
For the self-hosted desktop app, which is where the local model options live, here is the process.
- Open the Releases page on GitHub and download the installer for your system. There are one-click installers for macOS (both Apple Silicon and Intel) and Windows, plus AppImage and .deb builds for Linux.
- On macOS, the app is not notarized by Apple, so Gatekeeper will block it the first time. Move it into Applications, then either right-click the app and choose Open twice, or run
xattr -cr "/Applications/Open Generative AI.app"in Terminal once. After that first launch it opens normally. - On Windows, SmartScreen will flag the installer since it is not code-signed. Click “More info,” then “Run anyway.” It installs quietly with a Start Menu shortcut.
- On Linux, install the .deb package if it is available for your release, since it ships an AppArmor profile that avoids a sandbox permission issue on Ubuntu 24.04 and newer. If you are using the AppImage instead and it fails to launch, install
libfuse2first. - Open the app. You will be prompted for a Muapi API key on first use. Grab one from muapi.ai/access-keys if you plan to use the cloud models, or skip this step entirely if you only want the local, free options.
- To set up free local generation, go to Settings, then Local Models. The bundled sd.cpp engine installs with one click, after which you can download a model like Dreamshaper 8 and start generating from Image Studio by toggling the Local switch next to the model selector.
That is the whole setup. No Node.js or command line work required unless you want to build from source or run the Wan2GP server for the bigger local models.
How It Stacks Up Against the Platforms It Replaces
| Factor | Midjourney, Runway, Kling, etc. | Open Generative AI |
|---|---|---|
| Cost structure | Separate monthly subscription per platform | One free app, pay per generation only for the cloud models you actually use |
| Model access | Locked to that vendor’s own models | 400+ models from many vendors in one place |
| Self-hosting | Not available | Yes, full source available under MIT |
| Fully offline option | No | Only through the two local engines, and only for the models they support |
| Support | Vendor support team | Community, GitHub issues, Discord |
The most useful way to think about this app is as a universal remote for AI creative tools, not as a free replacement for their compute costs.
The Honest Limitations
You are not escaping the API layer for most models. If Muapi changes its pricing or a given model provider pulls access, this project inherits that directly. You are one layer removed from the actual model vendors, not connected to them.
The project markets itself as having no content filters and no prompt rejections at the app layer. That is accurate for the app itself, but your prompts still get routed to the underlying model providers through Muapi, and those providers, from OpenAI to Google to Kling AI, generally maintain their own usage policies regardless of which interface sends the request. Treat “no filters” as describing this specific app’s UI, not a guarantee about what any given model will actually produce.
It is a young, fast-moving project with 17 open issues and regular releases at the time of writing. Expect the occasional install hiccup, particularly around the macOS notarization and Linux sandbox issues covered above.
Full local, offline generation is limited to older or smaller models through sd.cpp, or to Flux Dev, Qwen Image, and a handful of video models through a self-run Wan2GP server that needs its own capable GPU. The headline models, Sora, Veo, Midjourney, and current-generation Kling, are cloud only.
Bottom Line
If you are currently paying for two or three separate AI image and video subscriptions just to compare outputs or pick the right model for a job, Open Generative AI genuinely solves that problem. One app, one interface, and access to nearly everything worth trying, with your own self-hosted install and full control over the data that stays on your machine. Just go in clear-eyed about the economics: the interface is free, but the frontier models behind it still run on someone else’s GPUs and someone else’s meter. Budget for Muapi credits if you want the marquee names, or lean on the bundled local engines if free and offline matters more to you than having Sora on tap.
If you have been juggling logins across four different AI video platforms just to find the right model for a shot, this is worth the ten minutes it takes to install. Share it with the person on your team still paying for three separate subscriptions to do what this does in one.
Just Being Resourceful! 
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