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Porting the Moebius 0.2B image inpainting model to run in the browser with Claude Code

ID

1986

Status

new

Published

23 Jun 2026, 7:43 AM

Fetched

27 Jun 2026, 8:23 PM

Provider

Simon Willison

Category

developer-ai

Original URL

https://simonwillison.net/2026/Jun/22/porting-moebius/

Source URL

https://simonwillison.net/atom/everything/

Excerpt

This morning on Hacker News I saw Moebius: 0.2B Lightweight Image Inpainting Framework with 10B-Level Performance, describing a small but effective inpainting model - a model where you can mark regions of an image to remove and the model imagines what should fill the space. The released model required PyTorch and NVIDIA CUDA, but since it described itself as 0.2B I decided to try and get it running using WebGPU in a browser. TL;DR: I got it working, and you can try the demo at simonw.github.io/moebius-web/. Read on for the details. The finished tool Here's a video demo of the finished tool: You can open any image in it (non-square images get letterboxed), highlight areas to remove, click the "Run inpaint" button and wait for the model to do its magic. A parallel agent side-project My main project for today was landing a major feature in Datasette: a UI for creating and altering tables, as a follow-up to the insert and edit rows feature I released last week. I was working on that in Codex Desktop (here's the PR) and often found myself spending 5-10 minutes spinning my fingers waiting for it to complete a mid-sized refactor or add the finishing touches to a change to the UI. (An amusing thing about coding agents is that the harder a problem is the more time you have to get distracted while you wait for them to finish crunching!) So I decided to spin up Claude Code in a terminal window and see how far I could get at porting Moebius to the web. Some agentic research to kick off the project My first step was to ask regular Claude about the feasibility of this project. In Claude.ai, which has the ability to clone repos from GitHub: Clone https://github.com/hustvl/Moebius/ and tell me if they published the code and weights to run this model anywhere (I hadn't spotted the link to the weights yet, that's tucked away in the "News" section.) Then: For Moebius what are the options for running it right now - Python and NVIDIA CUDA only or other options too? And: Muse on the feasibility of porting it to Transformers.js or similar and running it in a browser I like telling models to "muse on X", it's the shortest way I've found of expressing that I want them to contemplate a problem for me without providing them with a concrete goal. Here's that chat transcript. I copied out the last answer and saved it as research.md for Claude Code to read later. Claude suggested using ONNX Runtime Web on the WebGPU backend - the layer below the Transformers.js library I had suggested. That was enough to convince me it was worth setting Claude Code loose and seeing how far it could get. I usually start projects like this by gathering as much information as the coding agent might need as possible. Since I didn't expect this project to actually work I did everything in my /tmp folder: cd /tmp mkdir Moebius cd Moebius # Grab the Moebius python code git clone https://github.com/hustvl/Moebius # And the model weights (Claude figured this out): GIT_LFS_SKIP_SMUDGE=0 git clone \ htt