TRELLIS.2-4B — GGUF (f16)
GGUF (f16) conversions of microsoft/TRELLIS.2-4B
for the trellis2cpp /
ggml runtime — a CUDA-free, PyTorch-free C++ port of
the TRELLIS.2 image-to-3D pipeline. Load these directly; no safetensors conversion or
Python is needed at inference.
Files
| File | Pipeline stage | Source safetensors |
|---|---|---|
ss_flow_f16.gguf | Sparse-structure flow (64³ occupancy) | ss_flow_img_dit_1_3B_64_bf16 |
slat_flow_f16.gguf | Shape-SLAT flow, 512 fine | slat_flow_img2shape_dit_1_3B_512_bf16 |
slat_flow_1024_f16.gguf | Shape-SLAT flow, 1024 cascade | slat_flow_img2shape_dit_1_3B_1024_bf16 |
shape_dec_f16.gguf | Shape decoder → dual-grid fields | shape_dec_next_dc_f16c32_fp16 |
shape_enc_f16.gguf | Shape encoder (re-encode for texture flow) | shape_enc_next_dc_f16c32_fp16 |
tex_dec_f16.gguf | PBR texture decoder | tex_dec_next_dc_f16c32_fp16 |
tex_slat_flow_512_f16.gguf | Texture-SLAT flow, 512 | slat_flow_imgshape2tex_dit_1_3B_512_bf16 |
tex_slat_flow_1024_f16.gguf | Texture-SLAT flow, 1024 | slat_flow_imgshape2tex_dit_1_3B_1024_bf16 |
The image conditioning encoder (DINOv3) and the sparse-structure decoder are published separately: dinov3-vitl16-pretrain-lvd1689m-GGUF and TRELLIS-image-large-GGUF.
Conversion
Converted from the upstream bf16/fp16 safetensors to GGUF f16 (ggml ftype 1) with
the convert_*_to_gguf.py scripts in the trellis2cpp project. No weights were retrained
or modified — this is a format conversion only.
License
MIT, inherited from microsoft/TRELLIS.2-4B.
See LICENSE. Copyright (c) Microsoft Corporation.