Iris: Pure C Implementation of Flux 2 Image Generation Model Inference Pipeline
By
antirez
4mo ago· 16 min readenCode
100/100
Golden Brown
Bagelometer↗
Hand-rolled, kettle-boiled, baked to perfection. Worth every minute at the bakery.
Score100TypenewsSentimentneutral
Summary
Iris is a pure C implementation of an inference pipeline for image generation models, specifically designed for Flux 2 models. The project provides a lightweight, dependency-free solution for running image synthesis from text prompts using diffusion transformer models. It supports various model families, offers optional acceleration through MPS and BLAS, and includes features like LoRA support, negative prompts, and different sampling methods. The implementation emphasizes minimal dependencies and portability across different systems.
Key quotes
· 5 pulledIris is an inference pipeline that generates images from text prompts using open weights diffusion transformer models.
It is implemented entirely in C, with zero external dependencies beyond the C standard library.
The name comes from the Greek goddess Iris, messenger of the gods and personification of the rainbow.
MPS and BLAS acceleration are optional but recommended.
Under macOS, a BLAS API is part of the system, so nothing is required.
Flux 2 image generation model pure C inference. Contribute to antirez/iris.c development by creating an account on GitHub.
