Train LoRAs and Image Models Locally

DiffSynth-Studio is a Python diffusion model engine for developers and researchers who want to generate media and train models on their own hardware. It supports large models on consumer GPUs through memory offloading and quantization, with inference and training in the same framework. It's open source under Apache 2.0.

Diffusers is an open-source Python library for developers and researchers who want to run diffusion models on their own hardware or build generation features into an application. It uses PyTorch and supports image, video and audio generation. The library is licensed under Apache 2.0 and supports Apple Silicon.

FluxGym is a local web interface for training FLUX LoRAs on your own images, with support for GPUs with 12GB, 16GB or 20GB of VRAM. It's for people who want to customize an image model through a browser while retaining access to detailed training controls. It runs on Windows and Linux, with Docker support, and is open source under the MIT license.

NMKD Stable Diffusion GUI is a local AI image generator for people who want to create and edit images on a Windows PC. It combines Stable Diffusion generation with inpainting, LoRA training and image post-processing in a desktop interface. It's open source under GPL-3.0.

Kolors is a text-to-image model for people who want to generate photorealistic images on their own hardware, including work with Chinese prompts and Chinese cultural content. Developed by Kuaishou, it understands prompts in Chinese and English and can render text in both languages within generated images.

PixArt-Sigma is a text-to-image diffusion model that supports generation at 2K and 4K resolutions on your own machine or server. It's aimed at developers and researchers who want pretrained models they can run themselves, along with code for training and adapting them. The Python code is open source under Apache 2.0.

Sana is an open-source framework for running image and video generation on your own hardware, with image models small enough for laptop GPUs. It's aimed at creators who want local AI generation and developers who need training and inference pipelines for their own models. The code uses the Apache 2.0 license.

OmniGen is a local AI image generation model that handles text prompts, reference images, and image editing within one model. It's for creators who want to reuse subjects across images and developers building image tools on their own hardware. The code is open source under the MIT license.

Lumina-Image 2.0 is a local AI image generation framework for developers, researchers and people who want to generate images from text on their own hardware. It provides downloadable checkpoints, generation code and tools for adapting the model to your own image collections. The code uses the Apache 2.0 license.

Musubi Tuner is a Python toolkit for training LoRA adapters for image and video generation models on your own hardware. It's aimed at people who want to customize these models using their own datasets and are comfortable working with training scripts. It also includes image and video generation scripts for supported architectures.

diffusion-pipe is a local diffusion model training tool for people fine-tuning image and video models on their own GPU hardware. Its main distinction is that it can divide a model across several GPUs when it won't fit on one, while also distributing training work across GPUs. The Python project is open source under GPL-3.0 and uses DeepSpeed.

sd-scripts is a collection of Python scripts for training and generating images with models on your own hardware. It's aimed at people who want to customize image models through LoRA training or deeper fine-tuning and are comfortable working with scripts. The project is open source under the Apache 2.0 license.

SimpleTuner is an open-source toolkit for fine-tuning image, video and audio generation models on your own hardware or GPU servers. It's for creators and researchers adapting models to their datasets, and teams sharing training infrastructure. A web dashboard manages training jobs.

Stable Diffusion web UI (AUTOMATIC1111) is a browser interface for generating and editing images with models running on your own hardware. It's for artists and anyone who wants control over prompts, models and image variations. The software is open source under AGPL-3.0.

Kohya's GUI lets you train and fine-tune image generation models on your own GPU-equipped computer through a browser interface. It's for artists and model makers who want to teach a model a particular style or subject while controlling the training settings. The interface builds on Kohya's Stable Diffusion training scripts, with a command-line interface available too.

AI Toolkit (ostris) is an MIT-licensed training suite for people who want to fine-tune image and video models on their own hardware or a self-hosted server. It targets consumer NVIDIA GPUs and runs on Linux and Windows, including ARM64 Linux systems such as DGX Spark. An experimental installer also supports Apple Silicon Macs. GPU memory needs depend on the model and training task.

Draw Things is an AI image generation app for iPhone, iPad and Mac that keeps generation on your device and works offline. It's for people who want to create and edit images without sending that work to a cloud service, including artists developing character concepts or trying out apparel designs.

DiffusionBee is an open-source AI art app for Mac users who want to generate and edit images on their own computer. It runs Stable Diffusion offline, with image generation processed on the device. Model downloads require network access, and optional image uploads can send images externally. Its visual interface suits artists and designers who want local image tools without working through code.

OneTrainer is an open-source application for training diffusion models on your own machine, with dataset preparation and model previews in the same interface. It's for people adapting image or video models with their own training data. It runs on Windows, macOS and Linux under the AGPL-3.0 license.

PEFT is an open-source Python library for developers who want to adapt pretrained models on their own hardware with less compute and storage than full fine-tuning requires. It trains a small subset of parameters, often through adapters, while leaving the base model intact. It's licensed under Apache 2.0.

Real-ESRGAN is a local AI upscaler and restoration toolkit for people enlarging images or improving video, with dedicated models for anime illustrations and animation. It builds on ESRGAN and uses models trained entirely on synthetic data to address degraded images. The code is open source under the BSD 3-Clause license.