---
title: Overview
---

We offer several ways to install InvokeAI, each one suited to your
experience and preferences.

1. [InvokeAI source code installer](INSTALL_SOURCE.md)

    This is a script that will install Python, the Anaconda ("conda")
    package manager, all of InvokeAI's its essential third party
    libraries and InvokeAI itself. It includes access to a "developer
    console" which will help us debug problems with you and give you
    to access experimental features.

    When a new InvokeAI feature is available, even between releases,
    you will be able to upgrade and try it out by running an `update`
    script. This method is recommended for individuals who wish to
    stay on the cutting edge of InvokeAI development and are not
    afraid of occasional breakage.

    **Important Caveats**
    - This script is a bit cranky and occasionally hangs or times out,
    forcing you to cancel and restart the script (it will pick up where
    it left off).

2. [Manual Installation](INSTALL_MANUAL.md)

    In this method you will manually run the commands needed to install
    InvokeAI and its dependencies. We offer two recipes: one suited to
    those who prefer the `conda` tool, and one suited to those who prefer
    `pip` and Python virtual environments.

    This method is recommended for users who have previously used `conda`
    or `pip` in the past, developers, and anyone who wishes to remain on
    the cutting edge of future InvokeAI development and is willing to put
    up with occasional glitches and breakage.

3. [Docker Installation](INSTALL_DOCKER.md)

    We also offer a method for creating Docker containers containing
    InvokeAI and its dependencies. This method is recommended for
    individuals with experience with Docker containers and understand
    the pluses and minuses of a container-based install.

4. [Jupyter Notebooks Installation](INSTALL_JUPYTER.md)

    This method is suitable for running InvokeAI on a Google Colab
    account. It is recommended for individuals who have previously
    worked on the Colab and are comfortable with the Jupyter notebook
    environment.