Flux, the largest SOTA open source text-to-image model to date, developed by Black Forest Labs—the original team behind Stable Diffusion is now available on fal. Flux pushes the boundaries of creativity and performance with an impressive 12B parameters, delivering aesthetics reminiscent of Midjourney. To play around with the model

Today we released the second version of our single step GAN upscaler: AuraSR. We released AuraSR v1 last month and were encouraged by the community response so immediately started training a new version. AuraSR is based on the Adobe Gigagan paper using lucidrain’s implementation as a starting point. The

Open-source AI is in jeopardy. As community interest in AI models skyrocketed over the past year, we noticed that development of new open-source foundational models came to a halt. Some even boldly announced that open-source AI is dead. Not so fast! We are excited to present you the first release

Today we are releasing AuraSR, a 600M parameter upsampler model derived from the GigaGAN paper. This model can upscale low-res images to 4x the resolution, and can be applied repeatedly. We are publishing this model under a truly open source license. AuraSR excels in upscaling images generated by text-to-image models.

Greetings friends of fal! At fal, we are building the fastest and most reliable inference cloud for generative AI. We are thrilled to announce some major updates. Here’s what’s new: Stable Diffusion 3 Now Available Experience this state of the art text-to-image model from our friends at stability.

We’re excited to announce a simpler way to make our AI tools work better for you at fal.ai. Our latest feature lets enterprise users fine-tune their models with user preferences collected directly through their apps. This new service starts today, making it easier to tailor your model to

We are thrilled to announce our official integration with Vercel! This partnership marks a significant step forward in our commitment to offering a seamless, efficient web development experience. At fal, we believe it’s important to provide developers with all the tools they need to enable generative AI in their

In this blog post we would like to showcase fal’s real-time Stable Diffusion APIs that are powered by Latent Consistency Models (LCMs). These models have been getting a lot of hype lately because they allow you to generate images very quickly around 150ms as opposed to 10 seconds with

Effortlessly serve your Python functions through a managed web server.

We demonstrate how to speed up hyperparameter tuning using fal-serverless, so you can quickly explore the search space and find the best model configuration.

We are launching fal-serverless, a cloud based Python runtime that simplifies infrastructure for teams who are building data pipelines, analytics, ML training and inference.