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Creative & Generative Media Model Vision Experimental

TRELLIS

Image-to-3D Asset Generation

2,408,401 USERS
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TRELLIS

Interactive Playground

Mode

Input Image

Click or drag to upload an image

Latent Cfg Scale 3
24.579.510
Sparse Structure Cfg Scale 7.5
24.579.510
Latent Sampling Steps 25
1020304050
Sparse Structure Sampling Steps 25
1020304050
Seed

3D Result

3D preview will appear here Upload an image to generate a fully textured 3D asset.

About TRELLIS

TRELLIS is a 3D asset generation system that synthesizes high-quality 3D objects from a single image or a text prompt using a novel Structured LATent (SLat) representation. It uses rectified-flow transformers scaled up to 2 billion parameters and was trained on a curated dataset of 500,000 diverse 3D objects. A single TRELLIS model can decode the same latent into multiple output formats — meshes, radiance fields, and 3D Gaussians — and supports local editing that modifies specific 3D regions from a text or image prompt while preserving the rest of the structure. The system was adopted by NVIDIA AI Blueprints in September 2025.

Most prior 3D generators were locked into a single output format, which limited downstream reuse. By decoupling latent structure from decoder choice, TRELLIS lets users pick the representation that fits their pipeline — 3D Gaussians for real-time rendering, meshes for physical simulation, radiance fields for neural rendering — without retraining. Combined with photorealistic geometry and texture quality, this makes TRELLIS a practical building block for game studios, e-commerce, digital twins, and visual-effects pipelines, materially compressing the path from concept image to usable 3D asset.

Key capabilities

  • Single-image to textured mesh in under 10 seconds on a single A100
  • Structured LATent (SLat) representation as a unified 3D format
  • Outputs meshes, radiance fields, and 3D Gaussians from one model
  • Trained on 500K 3D objects with rectified-flow transformers up to 2B params
  • Adopted by NVIDIA AI Blueprints (Sept 2025)
Technology Stack
PyTorch Diffusion Models NeRF 3D Gaussians CUDA
Technology Stack
PyTorch Diffusion Models NeRF 3D Gaussians CUDA