Show HN: TRELLIS.2 image-to-3D running on Mac Silicon – no Nvidia GPU needed

https://github.com/shivampkumar/trellis-mac

53•shivampkumar•2h ago

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 convolution, SDPA attention for sparse transformers, and a Python-based mesh extraction replacing CUDA hashmap operations. Total changes are a few hundred lines across 9 files.

Generates ~400K vertex meshes from single photos in about 3.5 minutes on M4 Pro (24GB). Not as fast as H100 (where it takes seconds), but it works offline with no cloud dependency.

https://github.com/shivampkumar/trellis-mac

Comments

villgax•1h ago

That’s always been possible with MPS backend, the reason people choose to omit it in HF spaces/demos is that HF doesn’t offer an MPS backend. People would rather have the thing work at best speeds than 10x worse speeds just for compatibility.

refulgentis•50m ago

It’s always been possible, but it’s not possible because there’s no backend, and no one wants to it to be possible because everyone needs it 10x the speed of running on a Mac? I’m missing something, I think.

Reubend•35m ago

Are you saying the original one worked with MPS? Or are you just saying it was always theoretically possible to build what OP posted?

gondar•12m ago

Nice work. Although this model is not very good, I tried a lot of different image-to-3d models, the one from meshy.ai is the best, trellis is in the useless tier, really hope there could be some good open source models in this domain.

kennyloginz•4m ago

So much effort, but no examples in the landing page.

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Show HN: TRELLIS.2 image-to-3D running on Mac Silicon – no Nvidia GPU needed

Comments

Show HN: TRELLIS.2 image-to-3D running on Mac Silicon – no Nvidia GPU needed

Show HN: A lightweight way to make agents talk without paying for API usage

Show HN: A working reference implementation of context engineering

Show HN: Faceoff – A terminal UI for following NHL games

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