Looking to replace DALL·E with something free and open-source? These 8 tools are the best open alternatives in 2026 — most are self-hostable, so you keep full control of your data and pay no subscription.








| Alternative | License | Self-hostable | In one line |
|---|---|---|---|
| DALLE2-pytorch | MIT | ✓ Yes | Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch |
| Sana | Apache-2.0 | ✓ Yes | SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformer |
| imagen-pytorch | MIT | ✓ Yes | Implementation of Imagen, Google's Text-to-Image Neural Network, in Pytorch |
| mmagic | Apache-2.0 | ✓ Yes | OpenMMLab Multimodal Advanced, Generative, and Intelligent Creation Toolbox. Unlock the magic 🪄: Generative-AI (AIGC), easy-to-use APIs, awsome model zoo, diffusion models, for text-to-image generation, image/video restoration/enhancement, etc. |
| text-to-image | MIT | ✓ Yes | Text to image synthesis using thought vectors |
| custom-diffusion | — | ✓ Yes | Custom Diffusion: Multi-Concept Customization of Text-to-Image Diffusion (CVPR 2023) |
| HunyuanImage-2.1 | — | ✓ Yes | HunyuanImage-2.1: An Efficient Diffusion Model for High-Resolution (2K) Text-to-Image Generation |
| SkyPaint-AI-Diffusion | MIT | ✓ Yes | 基于Stable Diffusion优化的AI绘画模型。支持输入中英文文本,可生成多种现代艺术风格的高质量图像。| An optimized text-to-image model based on Stable Diffusion. Both Chinese and English text inputs are available to generate images. The model can generate high-quality images in several modern art styles |
Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch Its MIT license is permissive — free to use commercially, embed and modify. Because it is self-hostable, your data can stay entirely on your own infrastructure.
SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformer Its Apache-2.0 license is permissive — free to use commercially, embed and modify. Because it is self-hostable, your data can stay entirely on your own infrastructure.
Implementation of Imagen, Google's Text-to-Image Neural Network, in Pytorch Its MIT license is permissive — free to use commercially, embed and modify. Because it is self-hostable, your data can stay entirely on your own infrastructure.
OpenMMLab Multimodal Advanced, Generative, and Intelligent Creation Toolbox. Unlock the magic 🪄: Generative-AI (AIGC), easy-to-use APIs, awsome model zoo, diffusion models, for text-to-image generation, image/video restoration/enhancement, etc. Its Apache-2.0 license is permissive — free to use commercially, embed and modify. Because it is self-hostable, your data can stay entirely on your own infrastructure.
Text to image synthesis using thought vectors Its MIT license is permissive — free to use commercially, embed and modify. Because it is self-hostable, your data can stay entirely on your own infrastructure.
Custom Diffusion: Multi-Concept Customization of Text-to-Image Diffusion (CVPR 2023) Because it is self-hostable, your data can stay entirely on your own infrastructure.
HunyuanImage-2.1: An Efficient Diffusion Model for High-Resolution (2K) Text-to-Image Generation Because it is self-hostable, your data can stay entirely on your own infrastructure.
基于Stable Diffusion优化的AI绘画模型。支持输入中英文文本,可生成多种现代艺术风格的高质量图像。| An optimized text-to-image model based on Stable Diffusion. Both Chinese and English text inputs are available to generate images. The model can generate high-quality images in several modern art styles Its MIT license is permissive — free to use commercially, embed and modify. Because it is self-hostable, your data can stay entirely on your own infrastructure.
The top open-source alternative is DALLE2-pytorch — Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch. The full ranked list is above.
Yes. Every tool listed is open-source and free to use; most can be self-hosted so you keep full control of your data.
Most of these tools are designed to run on your own server or machine, giving you privacy and no subscription fees.
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