Open Generative AI

Generate unfiltered AI images, videos, and lip-sync animations with 200+ models via a self-hosted desktop app or web UI.

Generate unfiltered AI images, videos, and lip-sync animations with 200+ models via a self-hosted desktop app or web UI.

The gist

Open Generative AI is a free, open-source desktop and web application for creative media generation. Built by Anil-matcha and powered by Muapi.ai, it provides an unfiltered alternative to commercial AI platforms. The tool solves the problem of creative restriction by offering access to over 200 models for generating images, videos, and lip-synced animations without content filters, prompt rejections, or subscription fees, giving users full creative control.

What it does

  • Generate images from text or other images using over 50 different models.
  • Create videos from text prompts or animate still images with a selection of over 60 models.
  • Animate portrait images or sync lips on existing videos using an audio file and 9 dedicated models.
  • Run models for inference locally on your own machine using sd.cpp or a user-run Wan2GP server.
  • Build and run multi-step AI pipelines visually with a node-based workflow editor.
  • Access a wide range of popular and state-of-the-art models, including Flux, Kling, and Sora alternatives.

How it works

Architecture Diagram
Open Generative AI Architecture Diagram

Users interact with a GUI in a desktop app (macOS, Windows, Linux) or a hosted web version. You select a studio (Image, Video, Lip Sync), provide inputs like text prompts or media files, and choose from over 200 models. The desktop version can run models locally on your machine. Outputs are downloadable images or videos. The project is open-source and free to use, with the hosted version using the Muapi.ai backend.

Best for

This tool is best for developers and digital artists who want full, unrestricted control over generative AI media creation on their own hardware, free from the content filters and subscription costs of commercial platforms.

Watch out for

The desktop app is not notarized or code-signed, requiring manual security overrides during installation on macOS and Windows. Local inference for advanced models requires powerful hardware and, for some video models, setting up a separate Python server on a CUDA/ROCm-capable GPU machine.