> ## Documentation Index
> Fetch the complete documentation index at: https://docs.omnichar.org/llms.txt
> Use this file to discover all available pages before exploring further.

# Get started with Omnichar Studio

> Install Omnichar Studio, create a project, generate your first frame locally with Z-Image Turbo, then add a character and export the project.

This takes you from install to a first local render and an exported project. You need Python 3.11 or newer and, for local generation, a GPU. Z-Image Turbo, the model used below, fits in about 11.5GB of VRAM at 1024×1024.

**1. Install and start the app**

```bash theme={null}
git clone https://github.com/omnichar/OmniChar
cd OmniChar/core
./webui.sh --install --extra all
./webui.sh
```

On Windows, use `.\webui.bat` in place of `./webui.sh`. Open [http://127.0.0.1:8848](http://127.0.0.1:8848). See [Install](/app/install) for GPU-specific steps.

**2. Create a project**

On the home screen, name the project and click **Create**. A project is one portable folder holding your imported assets, every generated take and the graphs behind them, so you can move it, back it up or hand it to someone.

**3. Generate your first frame**

Add a **Z-Image Turbo** node to the canvas. If the model isn't on disk yet, the node's model popup downloads it with visible progress. Write a prompt and press **Run**.

Each run adds a new take to the frame and nothing is overwritten. Star the take you want to keep.

**4. Add a character**

Open the **Characters** panel and build a character on the canvas from a photo or two, or import a `.char` from [Omnichar Cloud](/cloud/getting-started) or ComfyUI. Then pick it on any model node that takes one. See [The .char character file](/characters) for which models do.

**5. Export the project**

From the home screen, **Export** zips the project into one file with its assets, takes and graphs. Whoever opens it can re-run the same pipeline.

## No GPU?

Add an API node, pick a hosted model such as GPT Image 2 or Seedance, and add your fal key in Settings. The result lands on the canvas as a take, next to your local renders. You can also run the whole app on a rented GPU with the [RunPod template](https://console.runpod.io/hub/template/c0qkyaypuv).

## Next steps

> **[Supported models](/app/models)**
>
> Every local model, with VRAM needs and file layout.

> **[Command-line options](/app/command-line)**
>
> Port, LAN access, low-VRAM mode and more.


## Related topics

- [Get started with Omnichar Cloud](/cloud/getting-started.md)
- [Get started with the Omnichar ComfyUI node](/comfyui/getting-started.md)
- [About Omnichar](/index.md)
- [The .char character file](/characters.md)
- [Omnichar Cloud overview](/cloud/overview.md)


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