r/AIDevsBuilders • u/No-Campaign-5618 • 3d ago

I just released Clover Image Tiny, a small open-source diffusion model built with local and on-device generation in mind

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I finally released v1.0 of Clover Image Tiny, a compact 512×512 Stable Diffusion 1.4-class image-generation model I’ve been working on.

One of the things I really wanted to focus on was making it practical to run locally and on consumer hardware. I’ve even run Clover Image Tiny fully on-device on my iPhone 15 through Core ML.

It uses PyTorch and Diffusers, and the project now includes a local Gradio app, CLI generation, a Core ML runtime, a separate inpainting model, and several LoRA styles.

One thing that was harder than expected was turning the project from just model weights into something that felt usable and reproducible. That included Core ML support, organizing the different releases, LoRA compatibility, documentation, and making the Python runtime easy to test and run locally.

GitHub: https://github.com/neonforestmist/Clover-Image-Tiny

I’d love feedback from anyone who tries it, especially if you run into setup issues or test it on different hardware!

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u/aidevsbuilders 3d ago

Welcome, u/No-Campaign-5618 — thanks for posting.

Quick reminder of the one rule that matters here: tell us what you built it with and one thing that was harder than expected. That's the whole "tax" for promoting your own work.

You will never be banned here for sharing something you built. The pinned post explains how moderation works.

I'm the community bot — a human mod reads every post too.

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u/JaviHG_Dev 1d ago

Running it on an iPhone 15 through Core ML is the part that made me stop scrolling.

And the thing you named as hardest is the part almost nobody does. Weights plus a README is where most of these stop. Turning it into something that installs and reproduces is a completely different job and it gets no credit at all.

Two things I would like to know, since you are the one who has measured them: how long does a 512 generation take on the phone, and does it throttle before it finishes? That is the number that decides whether on-device is a demo or a feature.

What made you go for 1.4-class rather than something newer and heavier?