Local when you can. Mutual when you can’t.
Run the full TripoSplat model on this device when its WebGPU and storage qualify,
or send the same job to a free MutualGPU provider from this page.
Qualified devices can also opt in to help process another person’s TripoSplat job.
Preparing your browser
- Checking WebGPU and storage…
Choose a starting image
Use a transparent PNG or WebP, or prepare an opaque photo locally before generation. The processor removes the background, frames the subject, and creates the official 1024px TripoSplat input.
Prepare a photo for TripoSplat
Opaque photos start background removal and the official subject crop automatically in this browser. Your pixels stay on this device; use the button to process again.
Choose an image to enable local processing.
Your spatial scene
A completed scene will appear here without leaving this page.
Choose where it runs
Use this device for private, browser-local WebGPU generation when it qualifies, or use MutualGPU without local GPU or storage requirements.
The result returns to this same viewer. Selecting remote mode sends the selected image to the MutualGPU exchange and assigned provider.
Engineering preview. A first local run may download about 6.5 GB and generation can take several minutes. MutualGPU wait time depends on network, service, and provider availability. Browser support and output quality vary.
Local model server
MutualGPU connection
Checking browser compatibility…
MutualGPU is online, but no TripoSplat provider is currently enrolled. Your image was not processed or queued. Try again shortly, or use the Contribute Compute bar below from a qualified WebGPU device.
What this browser is doing
Guided mode explains each stage in plain language. Technical details remain one click away.
- 01Source imageInspect alpha and prepare local pixels.READY
- 02Model packageVerify manifest, integrity, and browser cache.WAITING
- 03ConditioningPreprocess → DINOv3 → Flux VAE.WAITING
- 04Flow sampler20 official steps · 40 CFG DiT calls.WAITING
- 05Spatial decodeOctree occupancy → Gaussian decoder.WAITING
- 06Scene handoffEncode PLY / .splat and swap the viewer.WAITING
Copyable benchmark summary
Complete a generation to capture its timing and browser environment.
What likely caused this
Technical evidence and runtime event trail
Privacy: local mode keeps image processing and inference on this device. MutualGPU mode uploads the selected image to the exchange and assigned provider. Provider mode receives untrusted requestor images and uses the local model cache. TripoSplat model artifacts come from the official Hugging Face package unless you choose another server.
OPTIONAL / SHARE YOUR GPUBecome a MutualGPU providerChecking
Qualified Chrome devices can receive one remote requestor’s TripoSplat assignment at a time. Accepted work runs on this browser and can download the same 6.5 GB model cache while sustaining heavy GPU and power use for several minutes. The requestor identity is not disclosed, but every activity line shows the assignment ID, phase, and progress. The provider key stays in this page’s memory and is never saved. Closing the page interrupts the session. Only enable this in an operator-controlled browser.
Checking local WebGPU, model, and storage requirements…
REMOTE PROVIDER ACTIVITY · LAST 120 EVENTS
Provider is idle. Accepted assignments run on this browser for a MutualGPU requestor; each activity line identifies the remote task.
A monumental attempt to put CUDA-era 3D generation in reach of more people.
TripoSplat started as a CUDA-based 3D generation pipeline. With Codex GPT 5.6 Sol Ultra and GPT 5.6 Sol Max in Kiro, this project is porting that work to WebGPU—replacing the usual requirements for NVIDIA hardware, CUDA, terminal commands, environment setup, and local dependency installation with a browser-native workflow.
The goal is not a cosmetic port. It is an attempt to make advanced AI 3D generation radically more accessible: for GPUPoor MacBook users, students, independent developers, and anyone without an expensive GPU. When a browser passes the system check, they can generate a 3D asset locally on hardware they already own—no terminal, no installation, and no cloud GPU bill for inference.
This is still an engineering preview, with compatibility and quality under active qualification. But the direction is clear: keep powerful spatial-generation tools inspectable, local, and available to more builders.
Read the source, benchmarks, and open issues on GitHub