# ml-sharp-web — Apple's SHARP 3D Gaussian Splat Model Runs Entirely In Your Browser

> Apple's one-shot photo-to-3D Gaussian splat model, ported to ONNX and shipped as a 100% in-browser web app.

- Org: bring-shrubbery
- Date: 2026-05-03
- Category: repo, tool
- Source: https://github.com/bring-shrubbery/ml-sharp-web
- Canonical page: https://ai-tldr.dev/releases/bring-shrubbery-ml-sharp-web/

## In short

Show HN demo exports Apple's SHARP photo-to-3D model to ONNX and runs it client-side via WebAssembly. Drop in an image, get a downloadable .ply Gaussian splat, no server.

## What it is

ml-sharp-web is a TypeScript web app that runs Apple's SHARP — a 3D Gaussian splatting model that turns a single photo into a navigable 3D scene — entirely in the browser via ONNX Runtime Web. The author (bring-shrubbery) exported SHARP from Apple's official ml-sharp repo to ONNX and wrapped it in a Vite/React UI with a live splat viewer. A Show HN posted on May 3 hit 171 points and 43 comments.

## How it works

SHARP itself is a feedforward neural network that regresses a 3D Gaussian scene representation from a single image in one pass. The author exports the PyTorch model to ONNX (sharp_web_predictor.onnx, plus a ~2.4 GB weights sidecar), then loads it with onnxruntime-web compiled to WebAssembly. Inference runs locally on the user's CPU/GPU; the resulting splats are rendered with the GaussianSplats3D library and exportable as a standard .ply file.

## Why it matters

Browser inference for a 2.4 GB scene-synthesis model removes the cloud-GPU dependency that has gated most splatting demos. Anyone with Chrome and enough RAM can drop a photo in and walk around a 3D reconstruction. It is also a reference implementation for shipping large research models as static web apps via ONNX Runtime Web — relevant beyond view synthesis.

## Who it's for

graphics researchers, web developers, and anyone exploring on-device 3D reconstruction

## Try it

git clone https://github.com/bring-shrubbery/ml-sharp-web && bun install && bun dev

## Links

- [GitHub Repo](https://github.com/bring-shrubbery/ml-sharp-web)
- [Live Demo](https://ml-sharp-web.vercel.app/)
- [Show HN Discussion](https://news.ycombinator.com/item?id=47995037)
- [Apple SHARP (Upstream)](https://github.com/apple/ml-sharp)