Mage-Flow-Edit-Turbo: Microsoft’s 4B Image Editing Model

Overview

Mage-Flow-Edit-Turbo is a compact 4-billion-parameter image editing model built by microsoftthat applies text-guided edits to images through a shared architecture designed for both text-to-image generation and instruction-based editing. The model operates using a two-component stack: Mage-VAE (a lightweight latent tokenizer using one-step diffusion with anchor-latent KL regularization) and NR-MMDiT (a 4B Native-Resolution Multimodal Diffusion Transformer trained with rectified flow matching). The Turbo variant runs inference in just 4 steps, achieving 1.02 seconds per edit at 1024² resolution on a single A100 GPU while using peak memory of 18–20 GB. The model handles resolutions from 512 to 2048 pixels on any aspect ratio, including extreme 4:1 ratios. It is implemented using the diffusers library and released under an MIT license, making it freely usable for commercial purposes. The tokenizer achieves reconstruction fidelity matching FLUX.2-VAE while requiring approximately 22× fewer decode operations per pixel, removing the VAE as a performance...

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