that makes so much sense...I am exploring if I can find someone who has done this well...If not I'll try to do it myself.

The model needed about 15GB at peak during generation - the 4B model loads multiple sub-models (1.3B each for shape and texture flow). 8GB won't be enough, but both 24GB and 32GB both should be fine.

Thanks! Could it conceivably load the sub-models in series rather than parallel? 8 still won't be enough but I wonder if those with 16 could eke something out.

added! will add more, maybe even a GIF

i was able to get it in 3.5 mins from a single image on my 24gb m4 pro macbook

I'm still working on this to try to replicate nvdiffrast better. Found an open source port, might look it tonight

thanks!

I mean I can see that it's niche. Did not expect so many upvotes, but ig it's less niche than I tought

If you're not working with 3D on Apple Silicon this isn't relevant to you. For the subset of people who are, running this 4B parameter 3D generation model locally on a Mac was previously blocked by hard CUDA dependencies with no workaround.

Right but it is at most a couple of hours with claude code and posted on Sunday night.

Exactly, I know because I did the same thing!

I thought it was cool and then I found the open issue mentioned above, that convinced me its def something more people want.

It IS significantly slower, about 3.5 minutes on my MacBook vs seconds on an H100. That's partly the pure-PyTorch backend overhead and partly just the hardware difference.

For my use case the tradeoff works -- iterate locally without paying for cloud GPUs or waiting in queues.

IMO TRELLIS.2 is slightly different case from the HF models scenario. It depends on five compiled CUDA-only extensions -- flex_gemm for sparse convolution, flash_attn, o_voxel for CUDA hashmap ops, cumesh for mesh processing, and nvdiffrast for differentiable rasterization. These aren't PyTorch ops that fall back to MPS -- they're custom C++/CUDA kernels. The upstream setup.sh literally exits with "No supported GPU found" if nvidia-smi isn't present. The only reason I picked this up because I thought it was cool and no one was working on this open issue for Silicon back then (github.com/microsoft/TRELLIS.2/issues/74) requesting non-CUDA support.

You're right, thanks for flagging this, let me run something and push images

Hey, thanks for sharing this. I'm sure TRELLIS.2 definitely has room to improve, especially on texturing.

From what I've seen personally, and community benchmarks, it does fair on geometry and visual fidelity among open-source options, but I agree it's not perfect for every use case.

Meshy is solid, I used it to print my girlfriend a mini 3d model of her on her birthday last year!

Though worth noting it's a paid service, and free tier has usage limitations while TRELLIS.2 is MIT licensed with unlimited local generation. Different tradeoffs for different workflows. Hopefully the open-source side keeps improving.