# I made a 1-click app to run FLUX.2-klein on M-series Macs (8GB+ unified memory) : r/StableDiffusion
Been working on making fast image generation accessible on Apple Silicon. Just open-sourced it.
**What it does:**
\- Text-to-image generation
\- Image-to-image editing (upload a photo, describe changes)
\- Runs locally on your Mac - no cloud, no API keys
**Models included:**
\- FLUX.2-klein-4B (Int8 quantized) - 8GB, great quality, supports img2img
\- Z-Image Turbo (Quantized) - 3.5GB, fastest option
\- Z-Image Turbo (Full) - LoRA support
**How fast?**
\- ~8 seconds for 512x512 on Apple Silicon
\- 4 steps default (it's distilled)
**Requirements:**
\- M1/M2/M3/M4 Mac with 16GB+ RAM (8GB works but tight)
\- macOS
**To run:**
1. Clone the repo
2. Double-click Launch.command
3. First run auto-installs everything
4. Browser opens with the UI
That's it. No conda, no manual pip installs, no fighting with dependencies.
GitHub: [https://github.com/newideas99/ultra-fast-image-gen](https://github.com/newideas99/ultra-fast-image-gen)
The FLUX.2-klein model is int8 quantized (I uploaded it to HuggingFace), which cuts memory from ~22GB to ~8GB while keeping quality nearly identical.
Would love feedback.
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Source: [I made a 1-click app to run FLUX.2-klein on M-series Macs (8GB+ unified memory) : r/StableDiffusion](https://www.reddit.com/r/StableDiffusion/comments/1qdzj2t/i_made_a_1click_app_to_run_flux2klein_on_mseries/)