We offer several ways to install InvokeAI, each one suited to your experience and preferences. We suggest that everyone start by reviewing the hardware and software requirements, as they are the same across each install method. Then pick the install method most suitable to your level of experience and needs.
See the troubleshooting section of the automated install guide for frequently-encountered installation issues.
This fork is supported across Linux, Windows and Macintosh. Linux users can use either an Nvidia-based card (with CUDA support) or an AMD card (using the ROCm driver).
✅ This is the recommended installation method for first-time users.
This is a script that will install all of InvokeAI's 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.
This method is recommended for experienced users and developers.
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. In our hands the pip install
is faster and more reliable, but your mileage may vary.
Note that the conda installation method is currently deprecated and
will not be supported at some point in the future.
This method is recommended for those familiar with running Docker containers.
We 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.
Other Installation Guides#
You wil need one of the following:
- An NVIDIA-based graphics card with 4 GB or more VRAM memory.
- An AMD-based graphics card with 4 GB or more VRAM memory (Linux only)
- An Apple computer with an M1 chip.
** SDXL 1.0 Requirements* To use SDXL, user must have one of the following: - An NVIDIA-based graphics card with 8 GB or more VRAM memory. - An AMD-based graphics card with 16 GB or more VRAM memory (Linux only) - An Apple computer with an M1 chip.
Memory and Disk#
- At least 12 GB Main Memory RAM.
- At least 18 GB of free disk space for the machine learning model, Python, and all its dependencies.
We do not recommend the following video cards due to issues with their running in half-precision mode and having insufficient VRAM to render 512x512 images in full-precision mode:
- NVIDIA 10xx series cards such as the 1080ti
- GTX 1650 series cards
- GTX 1660 series cards
Created: November 12, 2022