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.

Downloads last month: 549

GGUF

Model size

0.5B params

Architecture

trellis2-shape-dec

Hardware compatibility

16-bit

Inference Providers NEW

Image-to-3D

This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for LocalAI-io/TRELLIS.2-4B-GGUF

Base model

microsoft/TRELLIS.2-4B

Quantized

(1)

this model