State-of-the-art 4B parameter model for high-fidelity 3D generation • O-Voxel representation • Full PBR materials • 3-60 second generation
Microsoft Research unveils TRELLIS.2, a 4B parameter model that revolutionizes image-to-3D generation with O-Voxel representation and full PBR materials. Achieves 3-60 second generation times at high resolution.
Generate high-quality 3D meshes with PBR materials directly in ComfyUI workflows. ComfyUI-TRELLIS2 wrapper makes image-to-3D accessible to the broader creative community with simple node-based interface.
Community developer camenduru releases TostUI integration for TRELLIS.2, enabling one-command local deployment. Run the entire 4B model stack with 100% local processing and zero external dependencies.
git clone https://github.com/microsoft/TRELLIS.2 && cd TRELLIS.2
Run ./setup.sh --new-env to create conda environment with all dependencies including PyTorch, CUDA, and flash-attn
pipeline = Trellis2ImageTo3DPipeline.from_pretrained('microsoft/TRELLIS.2-4B'); mesh = pipeline.run(image)[0]
Export to GLB format with PBR materials for use in Blender, Unity, or any 3D application
Large-scale 4 billion parameter flow-matching transformer for high-fidelity 3D generation with exceptional detail and accuracy.
Revolutionary field-free sparse voxel structure that handles arbitrary topology including open surfaces and non-manifold geometry.
Generates complete physically-based rendering materials: base color, roughness, metallic, and opacity for photorealistic results.
3 seconds at 512³, 17 seconds at 1024³, 60 seconds at 1536³ resolution on NVIDIA H100 GPU.
Textured mesh to O-Voxel in under 10s on CPU, O-Voxel to mesh in under 100ms on CUDA.
Fully open source under MIT license with training code, inference pipeline, and pretrained weights available.
"Good topology is probably 6-12 months away, but it's still fun as hell to drop in a complex character/object and get a quick reference."
"TRELLIS 2 is by far the best open source 3D generator. The ability to go from 2D design to 3D print-ready model is incredible."
"TRELLIS.2 generates high-resolution fully textured assets with exceptional fidelity and efficiency. The O-Voxel representation is a game changer."
TRELLIS.2 is a state-of-the-art large 3D generative model (4 billion parameters) designed for high-fidelity image-to-3D generation. It leverages a novel 'field-free' sparse voxel structure called O-Voxel to generate arbitrary 3D assets with complex topologies, sharp features, and full PBR materials.
TRELLIS.2 is incredibly fast on modern hardware. On an NVIDIA H100 GPU, it generates assets in approximately 3 seconds at 512³ resolution, 17 seconds at 1024³, and 60 seconds at 1536³ resolution.
O-Voxel is a revolutionary 'field-free' sparse voxel representation that breaks the limits of traditional iso-surface fields. It can handle open surfaces (like clothing), non-manifold geometry, and internal enclosed structures without lossy conversion, enabling true arbitrary topology support.
Yes! TRELLIS.2 generates GLB files that can be imported into Blender for 3D printing preparation. You should check wall thickness, manifold issues, normals, and scaling before sending to your slicer. The model works great for creating print-ready models from 2D designs.
TRELLIS.2 models complete PBR (Physically Based Rendering) materials including base color, roughness, metallic, and opacity. This enables photorealistic rendering and transparency support right out of the box.
TRELLIS.2 requires a Linux system with an NVIDIA GPU having at least 24GB of memory. The code has been verified on NVIDIA A100 and H100 GPUs. You'll also need CUDA Toolkit 12.4, Conda for dependencies, and Python 3.8+.
Yes! TRELLIS.2 is released under the MIT License. The inference code, pretrained 4B model weights, and web demo are all available. Training code is scheduled for release before December 31, 2025.
You can run TRELLIS.2 100% locally using Docker. The community has created TostUI integration: `docker run --gpus all -p 3000:3000 --name tostui-trellis2 camenduru/tostui-trellis2`. Alternatively, install via the GitHub repository setup script.
Microsoft Research • December 2024 • arXiv:2512.14692
We present TRELLIS.2, a large-scale 3D generative model that employs a novel 'field-free' sparse voxel structure termed O-Voxel and flow-matching transformers. Unlike previous methods relying on iso-surface fields which struggle with open surfaces or non-manifold geometry, our approach can reconstruct and generate arbitrary 3D assets with complex topologies, sharp features, and full physically-based rendering materials including transparency. Our 4B-parameter model generates high-resolution fully textured assets with exceptional fidelity and efficiency using vanilla DiTs and a Sparse 3D VAE with 16× spatial downsampling.
Novel 'field-free' sparse voxel structure that breaks the limits of iso-surface fields, enabling arbitrary topology handling without lossy conversion
Generates fully textured 3D assets at up to 1536³ resolution with exceptional fidelity using vanilla Diffusion Transformers
Models arbitrary surface attributes including base color, roughness, metallic, and opacity for photorealistic rendering
Instant optimization-free bidirectional conversion: mesh→O-Voxel in <10s on CPU, O-Voxel→mesh in <100ms on CUDA