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Trellis3D AI

Rating: 4.4
User Satisfaction: 88%
Trellis3D AI is a tool that generates 3D models from text or images for designers, developers, and creators so they can produce assets without manual 3D modeling.

Overview

Trellis3D AI is an AI-powered 3D asset generator that converts text prompts or images into fully usable 3D models. Instead of manually modeling objects in tools like Blender or Maya, you can describe or upload a reference image and let the system generate the object automatically.

The platform is based on the TRELLIS research model developed through collaboration between Microsoft Research and academic labs. It uses structured latent representations to generate detailed geometry and textures across several formats. The result is a 3D asset you can export and use in game engines, AR/VR apps, or design tools.

For teams building digital products, this can dramatically reduce the time needed to create prototype assets.

Traditional 3D modeling is slow and requires specialized skills. Even simple objects can take hours to build and texture.

Trellis3D AI reduces that barrier. Designers, indie developers, and content creators can generate usable assets in minutes instead of hours.

Details

Tool Launch / Founded Date

2024-12-01 (approx., research model release)

Best for

Indie game developers 3D artists and designers AR/VR creators Product design teams Creative technologists

Access Type

Freemium Paid subscription (credit-based generation)

Licensing Model

Assets generated are typically owned by the user depending on the platform plan Commercial usage generally allowed Users cannot resell generated assets as standalone marketplaces in some cases

Feature

  • Image-to-3D conversion — Upload a single image and generate a full 3D object automatically.
  • Text-to-3D generation — Describe an object with text and the AI produces the model.
  • Multiple export formats — Supports formats like GLB, OBJ, STL, GLTF, USDZ, and PLY.
  • High-detail geometry — Uses structured latent representations to capture shape and texture details.
  • PBR texture support — Generates physically based rendering textures suitable for modern engines.
  • Multi-view generation — Can reconstruct objects using multiple reference images.
  • Fast generation pipeline — Produces assets in minutes instead of hours of manual modeling.
  • Editable outputs — Assets can be refined in tools like Blender, Unity, or Unreal.
  • Community gallery — Users can browse or download generated models.

Pricing Tables

Basic
$8/month (billed annually)
  • 300 credits per month
  • 3 concurrent generation tasks
  • PBR textures supported
  • Unlimited daily downloads
  • Multiple export formats
Plus
$16/month (billed annually)
  • 1000 credits per month
  • Up to 10 concurrent tasks
  • Faster generation speeds
  • Advanced TRELLIS model access
  • Early access to new features
Pro
$48/month (billed annually)
  • 4000 credits per month
  • Unlimited concurrent tasks
  • Priority processing
  • Full export format support
  • Priority support

Analytics

Traffic Analysis

Domain Rating
8
Organic Traffic
3.97K
Majority Users
Russia

Visits Over Time

No visit data found.

Traffic Sources

No traffic data found.

Last Update Date: 2026-03-16

FAQ

Can I use Trellis3D AI models commercially?
Generally yes. Most platforms built on the TRELLIS model allow commercial use of generated assets. However, you should check the licensing rules of the specific service you’re using.
How many models can I generate per month?
It depends on your plan and credit allocation. For example, entry-level plans provide a few hundred credits per month, while higher tiers provide thousands.
Can I edit the generated 3D models?
Yes. You can export the models and edit them in tools like Blender, Maya, Unity, or Unreal Engine.
What file formats are supported?
Common export formats include OBJ, GLB, STL, GLTF, USDZ, and PLY, which work with most 3D software.
Does Trellis3D support APIs or developer workflows?
Some implementations provide API access so developers can integrate 3D generation into apps or pipelines.
Does the platform train on my content?
Public documentation doesn’t clearly state whether user uploads are used for training. Some deployments allow opting out.
Do I need powerful hardware to use it?
If you use the web service, no. If you run the open-source model locally, you’ll need a high-end NVIDIA GPU with at least ~16GB VRAM.

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