Newsletter
Join the Community
Subscribe to our newsletter for the latest news and updates
An open-source AI image generation app template built with Next.js, the AI SDK by Vercel, and Fal.
Fal Image Generator is an open-source AI image generation app template built by the Vercel team that combines Next.js 15, the Vercel AI SDK, and Fal to turn text prompts into images.
Fal Image Generator is a boilerplate application template that implements a complete image generation frontend and API route using the AI SDK's generateImage function. It takes a text prompt as its only required input and returns images from Fal models, with a single prompt able to target multiple models at once. The template is built on the Next.js App Router (version 15) and is maintained by Vercel with community contributions. It is designed to be deployed directly to Vercel or run locally with environment variables pulled from a linked Vercel project.
The app accepts a text prompt in a single input field and passes it to the AI SDK's generateImage function, which forwards it to Fal and returns the generated images to the UI. Running locally involves cloning the repository, installing dependencies, installing the Vercel CLI, linking the project with vercel link, pulling environment variables with vercel env pull, and starting the dev server with npm run dev — the app then runs on localhost:3000.
The template itself is open-source and free to use. It uses Fal for image generation, and Fal's pricing and free-tier availability apply to the actual image generation API calls.
The template uses Next.js 15 (App Router), the Vercel AI SDK, Tailwind CSS, and shadcn/ui. It relies on Fal as the image generation provider.
Yes, the repository includes a one-click "Deploy with Vercel" button that clones the project and sets up the Fal integration automatically on Vercel.
Clone the repo, run npm install, install the Vercel CLI globally, run vercel link to connect to your Vercel project, pull environment variables with vercel env pull, then run npm run dev and open localhost:3000.
