> For the complete documentation index, see [llms.txt](https://stablediffusion.gitbook.io/overview/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://stablediffusion.gitbook.io/overview/welcome-to-stable-diffusion.md).

# Welcome to Stable Diffusion

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**tip:** Stable Diffusion  is primarily used to generate detailed images conditioned on text descriptions, though it can also be applied to other tasks such as inpainting, outpainting, and generating image-to-image translations guided by a text prompt.
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## Abstract

Stable Diffusion is a latent diffusion model, a kind of deep generative neural network developed by the CompVis group at LMU Munich. The model has been released by a collaboration of Stability AI, CompVis LMU, and Runway with support from EleutherAI and LAION. In October 2022, Stability AI raised US$101 million in a round led by Lightspeed Venture Partners and Coatue Management.

Stable Diffusion's code and model weights have been released publicly, and it can run on most consumer hardware equipped with a modest GPU with at least 8 GB VRAM. This marked a departure from previous proprietary text-to-image models such as DALL-E and Midjourney which were accessible only via cloud services.

## Quick links

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[Technology](/overview/stable-diffusion-overview/technology.md)
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[License](/overview/stable-diffusion-overview/license.md)
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