Stability AI

Stability AI is a private company headquartered in London that develops generative AI models, systems that create new images, video, audio, 3D assets or text from a prompt. It was founded in 2019 by Emad Mostaque and Cyrus Hodes. Its name is tied to one model family, Stable Diffusion, a text-to-image model whose weights, the learned numbers that make up the trained network, were released for download in August 2022. That release made Stability AI one of the most visible advocates of open-weight AI, meaning models that anyone can download and run, as opposed to models available only through a company's own website or API.

Stable Diffusion is built on latent diffusion, a method published in December 2021 by Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser and Bjorn Ommer and accepted to CVPR 2022. A diffusion model learns to remove noise from an image step by step; to generate, it starts from pure noise and denoises repeatedly until an image appears. Running that process on every pixel is expensive. The latent diffusion paper instead trains an autoencoder, a network that compresses an image into a smaller representation called a latent and expands it back, and runs diffusion in that compressed space. The authors report that this greatly reduces compute compared with pixel-space diffusion while preserving detail. Text guides the process through cross-attention, a layer that lets the image representation look up information in an encoded version of the prompt.

The Stable Diffusion v1-4 model card shows the concrete numbers. Its autoencoder shrinks each side of the image by a factor of 8, so a 512 by 512 pixel image becomes a 64 by 64 grid with 4 channels. Prompts are encoded by a frozen CLIP ViT-L/14 text encoder. The checkpoint was initialized from v1-2 and fine-tuned for 225,000 steps at 512 by 512 resolution on LAION-Aesthetics v2 5+, a subset of the web-scraped LAION-2B English image and caption dataset. Training used 256 Nvidia A100 GPUs, and the card estimates the Stable Diffusion v1 models together used about 150,000 GPU hours and emitted about 11,250 kg of CO2 equivalent. The weights were released under the CreativeML OpenRAIL-M license, which permits commercial use but forbids listed harmful uses.

The company grew quickly and then hit trouble. In October 2022 it raised $101 million in a round led by Coatue and Lightspeed Venture Partners, which Wikipedia reports valued it at $1 billion. Costs outran revenue. TechCrunch, summarizing earlier reporting, said Stability was projected to make about $11 million in sales in 2023 while spending about $99 million a year on cloud computing from AWS, Google Cloud and CoreWeave, and had about $4 million in the bank in October 2023. Several Stable Diffusion researchers left; Wikipedia notes that departures from the Freiburg office preceded the founding of Black Forest Labs there in 2024. Mostaque resigned as CEO on March 23, 2024. On June 25, 2024, Prem Akkaraju, former CEO of the visual effects company Weta Digital, became CEO, Sean Parker became executive chairman, and suppliers agreed to forgive about $100 million of debt and release the company from about $300 million in future obligations.

Under new leadership the product line moved toward professional creative work. Stable Diffusion 3.5 was released on October 22, 2024, in three variants: Large with 8.1 billion parameters for 1-megapixel images, Large Turbo, a distilled version that generates in 4 steps, and Medium with 2.5 billion parameters, added October 29, which the company says needs 9.9 GB of graphics memory excluding text encoders. These models are built from transformer blocks, rather than the convolutional U-Net used in the original latent diffusion work. The company also lists video, audio and 3D models. On August 25, 2026, it announced a $76 million Series B with new investors including Electronic Arts, Sony Music Group, Universal Music Group, Warner Music Group and AMD Ventures, bringing funding since Akkaraju's arrival to $232 million including convertible notes.

Compared with closed image generators that are offered only as hosted services, Stability's open-weight approach lets users run models privately, modify them and build on them, and it created a large ecosystem of community fine-tunes and tools. The trade-off is control: once weights are public, the company cannot enforce safety filters on every copy, and it earns no revenue from most use. Its licensing has changed accordingly, from the permissive OpenRAIL-M license of 2022 to the Community License, which is free for non-commercial use and for organizations under $1 million in annual revenue, with larger organizations required to buy an enterprise license.

The largest open questions are legal. Artists filed a US lawsuit against Stability AI, Midjourney and DeviantArt in January 2023, and Getty Images sued in both the United States and England, alleging that millions of its photos were used for training. In the English case, Getty Images v Stability AI [2025] EWHC 2863 (Ch), Getty dropped its primary claims about training during the trial, and the court noted that training had taken place outside the UK. The court held that model weights can in principle be an article under UK copyright law, but that Stable Diffusion's weights were not an infringing copy because they never stored Getty's images. Getty partly succeeded on trademark claims over generated images showing its watermark, and permission to appeal the copyright point has been granted.

The model cards also list technical limitations: version 1 models struggle with legible text, complex compositions and faces, work best with English prompts, lose detail through the lossy autoencoder, and can reproduce images that were duplicated many times in training data. In practice, running a Stability model requires a graphics card with roughly 7 to 10 GB of memory for the smaller models, more for the largest, or use of the company's paid API and partner clouds, plus a check of the license that applies to the specific model version.