Hi HN, author here. SHARP is Apple's recent single-image 3D Gaussian splatting model (<a href="https://arxiv.org/abs/2512.10685" rel="nofollow">https://arxiv.org/abs/2512.10685</a>). Their reference code is PyTorch + a pretty heavy pipeline; I wanted to see if it could run in a browser with no server hop, so I exported the predictor to ONNX and ran it via onnxruntime-web with the WebGPU EP.<p>What works: drop in an image, get a .ply you can download or preview live, all on your machine — your image never leaves the tab. The model is large (~2.4 GB sidecar) so first load is slow on a cold cache, but inference itself is a few seconds on a recent Mac.<p>Caveats: SHARP's released weights are research-use only (Apple's model license, not the code's). I host the exported ONNX on R2 so thedemo "just works", but you can also export your own from the upstream Apple repo and upload locally.<p>Happy to talk about it in the comments :)