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Show HN: TRELLIS.2 image-to-3D running on Mac Silicon – no Nvidia GPU needed
Enables offline, cloud-independent image-to-3D model generation on Apple Silicon, removing the dependency on Nvidia GPUs and CUDA.
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AI Executive Synthesis
Enables offline, cloud-independent image-to-3D model generation on Apple Silicon, removing the dependency on Nvidia GPUs and CUDA.
This port addresses a significant hardware and ecosystem barrier for developers and designers working with 3D generation. By enabling Microsoft's TRELLIS.2 model to run on Apple Silicon without Nvidia GPUs or CUDA, it democratizes access to advanced image-to-3D capabilities. This reduces infrastructure costs and eliminates cloud dependencies, appealing to users with privacy concerns or limited internet access. While slower than high-end Nvidia GPUs, the offline capability and platform accessibility open new avenues for local development and creative workflows. This trend of optimizing complex AI models for diverse hardware platforms is crucial for broader adoption and innovation in fields like gaming, product design, and virtual reality.
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
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What is TRELLIS.2 image-to-3D running on Mac Silicon – no Nvidia GPU needed?
TRELLIS.2 image-to-3D running on Mac Silicon – no Nvidia GPU needed is analyzed by our AI as: Enables offline, cloud-independent image-to-3D model generation on Apple Silicon, removing the dependency on Nvidia GPUs and CUDA.. It focuses on This port addresses a significant hardware and ecosystem barrier for developers and designers working with 3D generation. By enabling Microsoft's T...
Where did TRELLIS.2 image-to-3D running on Mac Silicon – no Nvidia GPU needed originate?
Data for TRELLIS.2 image-to-3D running on Mac Silicon – no Nvidia GPU needed was aggregated directly from the Hacker News community ecosystem, representing raw developer and early-adopter sentiment.
When was TRELLIS.2 image-to-3D running on Mac Silicon – no Nvidia GPU needed publicly launched?
The initial public indexing or launch date for TRELLIS.2 image-to-3D running on Mac Silicon – no Nvidia GPU needed within our tracked developer communities was recorded on April 20, 2026.
How popular is TRELLIS.2 image-to-3D running on Mac Silicon – no Nvidia GPU needed?
TRELLIS.2 image-to-3D running on Mac Silicon – no Nvidia GPU needed has achieved measurable traction, logging over 80 traction score and facilitating 16 recorded discussions or engagements.
Which technical categories define TRELLIS.2 image-to-3D running on Mac Silicon – no Nvidia GPU needed?
Based on metadata extraction, TRELLIS.2 image-to-3D running on Mac Silicon – no Nvidia GPU needed is categorized under topics such as: TRELLIS.2 image-to-3D model, 4B parameter, Apple Silicon, PyTorch MPS.
What are some commercial alternatives to TRELLIS.2 image-to-3D running on Mac Silicon – no Nvidia GPU needed?
Our semantic intelligence engine identifies potential commercial alternatives in the SaaS space, such as Brew , which offers overlapping value propositions.
How does the creator describe TRELLIS.2 image-to-3D running on Mac Silicon – no Nvidia GPU needed?
The original author or development team describes the product as follows: "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 kernel..."
Community Voice & Feedback
Well done
Nothing much here. WTF is this near number 1 on the front page of HN?
So much effort, but no examples in the landing page.
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.
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.
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Hacker News Aggregated via automated community intelligence tracking.
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