Bria Technology |
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BRIA’s Technology

We're your holistic solution for all visual generation and modification requirements, whether it's access to foundation models, APIs, SDKs or Web integration. With a commitment to safe commercial use, we empower your organization and address your business challenges at scale while offering solutions with full liability coverage.



Exclusively trained from scratch on the largest licensed dataset built in collaboration with our data partners we guarantee the best quality outputs.


Legal & Safe

Trained on fully licensed data, we guarantee quality outputs with full liability, copyright protection, privacy and non-harmful content ensuring safe commercial use.

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Use It Your Way
Our technology is licensed and can be used for commercial use.

Licensed Source Models

Full suite of licensed models (source and weights) ready for use or fine-tuning, along with a comprehensive toolkit. Enhancing the research process by gaining flexibility, velocity and scale.

API’s Pipeline

Enhance your product with Generative AI capabilities by utilizing BRIA’s API and SDK for the quickest time to market. Allow your users to generate and customize real and synthetic visuals.

We built a machine that creates the largest licensed high quality visual collection in the world.

Our proprietary attribution engine: Our patented attribution engine rewards data contributors and creators based on their visual impact on every visual generation, thus nurturing a sustainable economy.

Algorithm Family Models


High resolution images and quality outcomes

BRIA 1.4

Best in class seamless integration of text-to-image,  inpainting and outpainting models

BRIA 1.2

Full compatible replacement for Stability v1.5

Brand Brain

Understands brand guidelines and spirit

Generative Search

Search capabilities for any visual repository without the need for tagging or metadata

Predictable and Controllable API Pipelines 

By delayering the visual to 5 elements, we allow customization of each layer in our APIs

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Safe and Compliant Technology

Being trained on safe, fully-licensed images, the model is your fast track to generation business impact, responsibly. Using them will save you time, workload and garnet you with velocity and scale. 

Bria’s licensed source model

An existing open-source model


Logos & Trademarks Safe

Not trained on trademarks or logos (e.g., logos of Apple, Coca-Cola or Nike), the model does not generate visuals that violate trademarks or logos.

Bria’s licensed source model

Apple on a wooden desk

An existing open-source model

Apple on a wooden desk


Copyrights Safe

Not trained on copyright-protected or fictional-characters visuals (e.g., Yoda, Superman, or Super Mario), the model does not generate images that violate copyrights.

Bria’s licensed source model


An existing open-source model



Misinformation and NSFW Protected

Our model mitigates harmful and fake visuals as well as misinformation protection. Additionally, our images are marked as AI-generated

Bria’s licensed source model

Prince singer

An existing open-source model

Prince singer

Seamless Swap-In for Higher Quality

Version Bria 1.2 was built to replace stability 1.5. 

BRIA V1.2 Model

Existing text-to-image models may expose users to considerable legal risks or exposure to NSFW content.

BRIA’s safe solution is seamlessly integrated in a “plug and play” manner unlocking all available extensions and pipelines.

To achieve this, we have adopted the popular and widely-used architecture known as latent diffusion model. Bria 1.2 is a vanilla application of such architecture (equivalent to Stable Diffusion v1.5), and we offer an improved algorithm with Bria v1.4. We recommend plug-and-play Bria 1.2 for immediate full legal compliance and generation safety. For better results and full legal compliance and generation safety, we recommend adopting Bria 1.4.

We utilise a latent diffusion model architecture consisting of several components: a text encoder called CLIP ViT-L/14, a perceptual encoder-decoder known as VAE, and a UNet backbone. In this model, images are transformed into latent representations through the VAE, whereas textual captions are encoded using the text encoder. These encoded captions are then integrated into the UNet backbone using cross-attention. The optimization objective is similarity between the noise added to the latent representation and the UNet prediction

Coming soon: Version Bria 2.1 was built to replace stability XL.

Bria 1.2

Stability 1.5


Prompt: Mountain


Prompt: Burger

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