Open Text-to-Image Models

CogView4 is a text-to-image model for image creators and developers who want to generate images on their own hardware. It accepts Chinese and English descriptions and can include Chinese text in the results.

PixArt-Sigma generates images from text prompts on your own machine or a self-hosted server. It's for developers and researchers who want downloadable image models and the code to train their own.

Qwen-Image generates images from text and edits existing pictures. It's for creators and developers who want to run an image model on their own hardware, especially for work that needs readable text within images.

4M is a framework for researchers and developers who want to train and run models that combine images, text and other visual information. A single model can perform vision tasks and generate images from mixed or partial inputs.

InstantID generates personalized portraits from a single reference photo without training a model for each person. Creators and developers can retain a person's facial identity while changing the image through text prompts. Its required InsightFace face models are restricted to non-commercial research.

Stable Diffusion 3.5 is a text-to-image model family for developers building image tools and creators producing visual work on their own infrastructure. Prompts can describe the subject and composition across photographic, painted, line-art and 3D styles.

Chroma is a text-to-image model for people who want to generate images from written prompts. Its weights are available in Safetensors format.

UNO is a local AI image generation framework for researchers and creators who want to preserve subjects from reference images in generated scenes. One model handles both single-subject images and compositions with several subjects.

ControlNet adds visual guidance to Stable Diffusion for artists and developers who need generated images to follow a reference's layout or shape. It lets a sketch, pose or scene map guide the result alongside a text prompt.

IC-Light changes the lighting in existing images for people editing portraits, product shots, or other foreground subjects. It lets you explore different lighting conditions using a subject image as the starting point.

Sana is a local AI image and video generation framework for creators and developers who want to generate media on their own hardware. It includes training and inference tools for working with its diffusion models.

BrushNet fills selected areas of an image using a text prompt while retaining the surrounding content. It's for developers and researchers who want local image editing with pretrained diffusion models.

VAR is an image generation research toolkit for researchers and developers studying autoregressive models as an alternative to diffusion. It generates images through next-scale prediction, building finer detail across successive image scales.

IP-Adapter adds reference-image prompting to Stable Diffusion for artists and developers who want to guide generation with an image rather than describe every detail in words. It works with an existing text-to-image model and can combine image references with text prompts.

PhotoMaker generates personalized portraits and artwork from reference images and text prompts. It's for people creating photos or avatars that retain a person's recognizable features across different settings and styles.

HunyuanImage is Tencent's text-to-image model for people who want to generate images on their own hardware. It handles detailed scene descriptions, including requests for lettering within an image.

Step1X Edit edits existing images from written requests. It's for developers and researchers who want to run image editing on their own hardware, with control over the model and specialized training.

Stable Diffusion 1.5 is an AI image generation model for artists and developers who want to create artwork or explore design ideas on their own hardware. It can start with a text prompt or modify an existing picture.

Kolors generates photorealistic images from text for creators and developers who want to run image generation on their own hardware. Developed by Kuaishou, it supports Chinese and English prompts, including descriptions of Chinese cultural content.

FLUX.1 is a family of image models for developers and creators who want to generate and edit images on their own hardware or servers.

StyleGAN3 is NVIDIA's local AI image generation and training software for researchers and developers. Its architecture addresses generated detail that stays fixed to pixel positions instead of following the depicted objects as they move.

HunyuanWorld generates explorable 3D environments from text prompts or images. It's for game developers, VR creators and researchers who need scene geometry for interactive content or physical simulation.

HunyuanDiT is a local text-to-image model for people generating images from Chinese or English prompts. It handles detailed descriptions and Chinese cultural references, including poetry, idioms, food and architecture.

Stable Diffusion XL is an image generation model for creators and developers who want to produce images on their own hardware or servers. You can start with a text prompt or use an existing image as input.

Uni MoE is a family of multimodal AI models for researchers working with language, visual material and audio together. Its Omni model can reason across combined inputs and answer questions about their content.

HiDream-I1 generates images from text prompts for creators and developers who want to work on their own hardware or add image generation to an application.

Janus-Pro is a multimodal AI model for developers and researchers who want to interpret images and generate pictures on their own hardware. It combines both tasks in one model.

InfiniteYou generates images from a reference face and a text prompt while preserving the person's facial identity. It's a local AI framework for researchers studying personalized image generation, with model use restricted to academic research.

Lumina-Image 2.0 generates images from text on your own hardware. It's for developers, researchers and people who want a model they can use in visual workflows or adapt with their own image collections.