Converted model weights for Geo Gen's native prompt-to-mesh mode on Apple
silicon and macOS 14 or newer. The bundle contains 40 Core ML packages,
the CLIP tokenizer, licences, and a SHA-256 inventory (bundle.json).
Download size is approximately 3.28 GB. No Python inference runtime is needed
by the TouchDesigner operator.
The complete folder is required: text encoder, coarse shape flow/decoder, sparse detail flow, mesh decoder, and a separate Gaussian appearance decoder. The native helper performs sampling, sparse routing, FlexiCubes extraction, fragment removal, mesh simplification, appearance rendering, and UV baking. The model packages alone are not a standalone generation application.
In an AML release supporting this bundle, choose Geo Gen → Input → Prompt, then Manage Models → TRELLIS Text → Download. Alternatively, download this repository without changing its directory layout and set Prompt Model Folder to that folder. The image-only TripoSR/SF3D downloads do not supply these models.
Start with 8 Shape Steps, 8 Detail Steps, Mesh Detail Standard, and a 1024²
texture. A complete a mouse generation at seed 42 took 112.5 seconds inside
TouchDesigner on an Apple M4 with 24 GB memory, with models already loaded. First-time
Core ML compilation takes longer. This is a development-machine measurement,
not a speed guarantee for other prompts or hardware. Increasing steps, mesh
detail, and texture resolution trades time and memory for quality.
Both mesh-detail settings extract the full learned 256³ surface; Standard targets at most 60,000 triangles and a quarter of the original count, with a geometric error limit that can retain more triangles when necessary. Minimum Piece Size defaults to 0.1% of the largest connected piece's triangle count. Set it to 0 when small detached details are intentional. Generation is approximate: meshes may contain openings or other defects, and are not guaranteed printable or watertight. Colours use the appearance decoder, not the mesh head's auxiliary colour channels. Albedo is sampled per texel from rendered appearance views. The normal output is the geometric surface normal.
No fine-tuning or substitute model weights were used. Source revisions:
microsoft/TRELLIS-text-large,
4aad9f4a110329a410974d7f41ce5333a9a1fc87.JeffreyXiang/TRELLIS-image-large,
25e0d31ffbebe4b5a97464dd851910efc3002d96.openai/clip-vit-large-patch14,
32bd64288804d66eefd0ccbe215aa642df71cc41.Conversion recipes are in labs/trellis-text of TD Apple ML. Converted with
coremltools 9.0, using mixed source precision and explicit float32 attention
where required. The helper selects tested CPU/GPU compute paths per package;
changing those paths can produce incorrect results. Native random seeds are
repeatable within this implementation but do not reproduce NumPy's noise
stream. Full equivalence with the upstream CUDA pipeline has not been established.
The current helper supports at most 32,768 occupied detail cells and 8,192 pooled attention tokens. It reports an error rather than truncating larger results; use another seed or the coarse preview in that case.
TRELLIS weights and adapted inference code: Microsoft Corporation, MIT
(TRELLIS-LICENSE.txt). CLIP: OpenAI, MIT (CLIP-LICENSE.txt). The conversion
does not change the upstream model licences. Native geometry libraries are
distributed and attributed separately with the AML plugin.
flow_mixed_attn32.mlpackage/Data/com.apple.CoreML/weights/weight.bin 1.1 GBtext_fp32.mlpackage/Data/com.apple.CoreML/weights/weight.bin 492 MBslat_blocks_0.mlpackage/Data/com.apple.CoreML/weights/weight.bin 181 MBslat_blocks_1.mlpackage/Data/com.apple.CoreML/weights/weight.bin 181 MBslat_blocks_2.mlpackage/Data/com.apple.CoreML/weights/weight.bin 181 MBslat_blocks_3.mlpackage/Data/com.apple.CoreML/weights/weight.bin 181 MBslat_blocks_4.mlpackage/Data/com.apple.CoreML/weights/weight.bin 181 MBslat_blocks_5.mlpackage/Data/com.apple.CoreML/weights/weight.bin 181 MBdecoder.mlpackage/Data/com.apple.CoreML/weights/weight.bin 147 MBslat_input.mlpackage/Data/com.apple.CoreML/weights/weight.bin 76 MBslat_output.mlpackage/Data/com.apple.CoreML/weights/weight.bin 19 MBappearance_block_0.mlpackage/Data/com.apple.CoreML/weights/weight.bin 14 MBappearance_block_1.mlpackage/Data/com.apple.CoreML/weights/weight.bin 14 MBappearance_block_10.mlpackage/Data/com.apple.CoreML/weights/weight.bin 14 MBappearance_block_11.mlpackage/Data/com.apple.CoreML/weights/weight.bin 14 MBappearance_block_2.mlpackage/Data/com.apple.CoreML/weights/weight.bin 14 MBappearance_block_3.mlpackage/Data/com.apple.CoreML/weights/weight.bin 14 MBappearance_block_4.mlpackage/Data/com.apple.CoreML/weights/weight.bin 14 MBappearance_block_5.mlpackage/Data/com.apple.CoreML/weights/weight.bin 14 MBappearance_block_6.mlpackage/Data/com.apple.CoreML/weights/weight.bin 14 MBappearance_block_7.mlpackage/Data/com.apple.CoreML/weights/weight.bin 14 MBappearance_block_8.mlpackage/Data/com.apple.CoreML/weights/weight.bin 14 MBappearance_block_9.mlpackage/Data/com.apple.CoreML/weights/weight.bin 14 MBmesh_block_0.mlpackage/Data/com.apple.CoreML/weights/weight.bin 14 MBmesh_block_1.mlpackage/Data/com.apple.CoreML/weights/weight.bin 14 MBmesh_block_10.mlpackage/Data/com.apple.CoreML/weights/weight.bin 14 MBmesh_block_11.mlpackage/Data/com.apple.CoreML/weights/weight.bin 14 MBmesh_block_2.mlpackage/Data/com.apple.CoreML/weights/weight.bin 14 MBmesh_block_3.mlpackage/Data/com.apple.CoreML/weights/weight.bin 14 MBmesh_block_4.mlpackage/Data/com.apple.CoreML/weights/weight.bin 14 MBmesh_block_5.mlpackage/Data/com.apple.CoreML/weights/weight.bin 14 MBmesh_block_6.mlpackage/Data/com.apple.CoreML/weights/weight.bin 14 MBmesh_block_7.mlpackage/Data/com.apple.CoreML/weights/weight.bin 14 MBmesh_block_8.mlpackage/Data/com.apple.CoreML/weights/weight.bin 14 MBmesh_block_9.mlpackage/Data/com.apple.CoreML/weights/weight.bin 14 MBmesh_up_0.mlpackage/Data/com.apple.CoreML/weights/weight.bin 10 MBmesh_up_1.mlpackage/Data/com.apple.CoreML/weights/weight.bin 2 MBappearance_output.mlpackage/Data/com.apple.CoreML/weights/weight.bin 1 MBappearance_input.mlpackage/Data/com.apple.CoreML/weights/weight.bin 28.4 kBmesh_input.mlpackage/Data/com.apple.CoreML/weights/weight.bin 28.4 kBmicrosoft/TRELLIS-image-largeHave the files? Submit a torrent.
Submit a torrentHave the complete files and permission to share them? Replace the example folder path. The script checks the files, makes a torrent and submits its magnet and checksums. Keep your torrent client seeding. Get your community key from your settings, and read the script before running it.
curl -fsSL https://pirateface.co/package.sh | bash -s -- --repo mickeyvanolst/trellis-text-coreml ./model-folder