DiffusionBee icon

DiffusionBee

com.linerai.liner · Developer Tools · v1.5.1
Native Version Spotted 2 devices · 353.8 MB · Impact: 45/100
Native Version Spotted

Apple Silicon version latest seen at v1.5.1 · Reported by 2 Macs in the community.

Sighting data is community-sourced — version availability and pricing should be verified with the developer.

About This App

DiffusionBee is a user-friendly desktop application that brings Stable Diffusion and related generative AI models to macOS with a one-click installer. It lets users generate images from text prompts, perform image-to-image transformations, and apply tools like inpainting, outpainting, and upscaling entirely offline on their local machine without cloud dependencies. The app is aimed at beginners and casual users who want to create AI art without wrestling with Python, terminal commands, or GPU configuration. DiffusionBee supports both Intel and Apple Silicon Macs, with native Apple Silicon builds optimised for M-series performance. A native build has been confirmed running on Macs in the Rosetta Check community.

Versions Seen 1 version
v1.5.1

AI Recommendation

1 suggestion
DiffusionBee AI
https://github.com/divamgupta/diffusionbee-stable-diffusion-ui/releases

A native Apple Silicon build of DiffusionBee is available and confirmed working. To update, visit the official DiffusionBee GitHub releases page and download the latest arm64 release marked with Apple Silicon support — look for a filename like DiffusionBee_MPS_arm64 followed by the version number. Open the downloaded DMG file, drag the DiffusionBee icon into your Applications folder, and the native build will replace any older Intel version. The main website (diffusionbee.com/download) may not always link to the absolute latest version, so going directly to GitHub ensures you get the most current native build with full feature support including Flux model generation. After installing, your existing preferences, models, and saved images will carry over without any manual migration needed. You should see noticeably better performance and reduced CPU load when generating images compared to running under Rosetta.