Run TRELLIS.2 Image-to-3D generation natively on Apple Silicon

In plain words

Run TRELLIS.2 is a port of Microsoft's image-to-3D model that runs natively on Apple Silicon using PyTorch MPS instead of requiring CUDA. It converts single photographs into detailed 3D meshes with approximately 400,000 vertices in about 3.5 minutes on M4 Pro hardware. The project replaces GPU-specific operations with pure-PyTorch alternatives, enabling offline 3D generation without cloud dependency. It is designed for developers and creators working on Apple computers who need local 3D model generation from images.

written from the facts on this page · September 2026

From the sources

Contribute to shivampkumar/trellis-mac development by creating an account on GitHub.

This is a port of Microsoft's TRELLIS.2 — a state-of-the-art image-to-3D model — from CUDA-only to Apple Silicon via PyTorch MPS. No NVIDIA GPU required. Generates 400K+ vertex meshes with baked PBR textures from a single image in ~5 minutes 13 seconds on M4 Pro (24GB, cold start, weights cached, cool machine, pipeline type 512 ). About 3m 20s of that is actual generation and baking; the remaining ~1m 45s is pipeline load that happens once per Python process. Output is a GLB with base-color, metallic, and roughness textures — ready for use in 3D applications. # Clone this repo git clone https://github.com/shivampkumar/trellis-mac.git cd trellis-mac # (Recommended) Download the Xcode Metal…from github.com

In the maker’s words, at launch

I ported Microsoft's TRELLIS.2 (4B parameter image-to-3D model) to run on Apple Silicon via PyTorch MPS. The original requires CUDA with flash_attn, nvdiffrast, and custom sparse convolution kernels: none of which work on Mac. I replaced the CUDA-specific ops with pure-PyTorch alternatives: a gather-scatter sparse 3D…

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