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How to Install TRELLIS 2: Complete Setup Guide for All Platforms (2026)
2026/04/17
5 min read

How to Install TRELLIS 2: Complete Setup Guide for All Platforms (2026)

Step-by-step guide to installing TRELLIS 2 locally on Windows, Linux, and macOS. Covers GPU requirements, Python setup, ComfyUI integration, Docker, and troubleshooting common installation issues.

Last updated: April 14, 2026

TRELLIS 2 by Microsoft Research is an open-source AI model for generating high-quality 3D assets from text or images. This guide walks through every installation method — from a quick local setup to Docker and ComfyUI integration — so you can start generating 3D models on your own hardware.

If you'd rather skip the setup, you can use TRELLIS 2 online with no installation required.

System Requirements

Before installing TRELLIS 2, verify your system meets these requirements:

Minimum Requirements
ComponentMinimumRecommended
GPUNVIDIA with 8GB VRAMNVIDIA with 16GB+ VRAM
RAM16 GB32 GB
Storage10 GB free20 GB free (SSD preferred)
Python3.103.11
CUDA11.812.1+
OSLinux (Ubuntu 20.04+)Linux (Ubuntu 22.04+)

GPU Compatibility

GPU SeriesExample GPUsMax ResolutionPerformance
RTX 30/40 SeriesRTX 3060, 4070, 4080, 40901536³Excellent
RTX 20 SeriesRTX 2060, 2070, 20801024³Good
GTX 16/10 SeriesGTX 1660, 1080, 1080 Ti512³Acceptable
Server GPUsA100, V100, H1001536³Excellent

Note: AMD and Apple Silicon GPUs are not officially supported. AMD users can try the ROCm build, but expect limited compatibility. Mac users should use TRELLIS 2 online instead.

Installation Methods

Choose the method that fits your setup:

MethodDifficultyBest ForSetup Time
Linux (Native)IntermediateMost setups15-30 min
Windows (Native)IntermediateWindows users15-30 min
ComfyUI IntegrationIntermediateComfyUI users20-40 min
DockerAdvancedReproducible environments10-20 min
One-Click InstallerBeginnerWindows, quick setup5-10 min

Method 1: Linux Installation

Step 1: Install Prerequisites

# Update system packages
sudo apt update && sudo apt upgrade -y

# Install Python 3.11 and pip
sudo apt install python3.11 python3.11-venv python3-pip -y

# Install CUDA toolkit (if not already installed)
# For CUDA 12.1:
wget https://developer.download.nvidia.com/compute/cuda/12.1.0/local_installers/cuda_12.1.0_530.32.01_linux.run
sudo sh cuda_12.1.0_530.32.01_linux.run

# Verify CUDA installation
nvcc --version
nvidia-smi

Step 2: Clone the Repository

# Clone TRELLIS 2
git clone https://github.com/microsoft/TRELLIS.2.git
cd TRELLIS.2

Step 3: Create Virtual Environment

# Create and activate virtual environment
python3.11 -m venv venv
source venv/bin/activate

# Upgrade pip
pip install --upgrade pip

Step 4: Install Dependencies

# Install PyTorch with CUDA support
pip install torch torchvision --index-url https://download.pytorch.org/whl/cu121

# Install TRELLIS 2 dependencies
pip install -r requirements.txt

Step 5: Download Model Weights

# Download pre-trained weights from Hugging Face
python download_weights.py

This downloads approximately 8 GB of model weights. The weights are saved to the weights/ directory.

Step 6: Verify Installation

# Run a quick test
python infer.py --text_prompt "a red cube" --output_path test_output.glb

If the installation is successful, you'll find test_output.glb in the project directory.

Method 2: Windows Installation

Option A: One-Click Installer (Recommended for Beginners)

The community provides a one-click installer that handles most setup automatically:

  1. Download the installer from the TRELLIS Windows installer repository
  2. Extract the archive to a folder with no spaces in the path (e.g., C:\TRELLIS2)
  3. Run install.bat as administrator
  4. Wait for the installation to complete (10-15 minutes)
  5. Run run.bat to start the web interface

Option B: Manual Installation

Step 1: Install Prerequisites

  1. Install Python 3.11 (check "Add to PATH")
  2. Install Git for Windows
  3. Install CUDA Toolkit 12.1
  4. Install Visual Studio Build Tools (select "Desktop development with C++")

Step 2: Clone and Set Up

# Clone the repository
git clone https://github.com/microsoft/TRELLIS.2.git
cd TRELLIS.2

# Create virtual environment
python -m venv venv
.\venv\Scripts\activate

# Upgrade pip
pip install --upgrade pip

Step 3: Install Dependencies

# Install PyTorch with CUDA support
pip install torch torchvision --index-url https://download.pytorch.org/whl/cu121

# Install dependencies
pip install -r requirements.txt

Step 4: Download Weights and Test

# Download model weights
python download_weights.py

# Run test
python infer.py --text_prompt "a red cube" --output_path test_output.glb

Method 3: ComfyUI Integration

TRELLIS 2 can be integrated into ComfyUI for node-based 3D generation workflows.

Step 1: Install ComfyUI

If you don't have ComfyUI installed:

git clone https://github.com/comfyanonymous/ComfyUI.git
cd ComfyUI
pip install -r requirements.txt

Step 2: Install TRELLIS 2 Custom Nodes

cd ComfyUI/custom_nodes/
git clone https://github.com/comfyui-extensions/ComfyUI-TRELLIS.2.git
cd ComfyUI-TRELLIS.2
pip install -r requirements.txt

Step 3: Download Model Weights

Place the TRELLIS 2 weights in the ComfyUI models directory:

# Create directory if it doesn't exist
mkdir -p ComfyUI/models/trellis/

# Download weights
python ComfyUI/custom_nodes/ComfyUI-TRELLIS.2/download_weights.py \
  --output_dir ComfyUI/models/trellis/

Step 4: Start ComfyUI

cd ComfyUI
python main.py

Access the ComfyUI web interface at http://localhost:8188 and search for TRELLIS nodes in the node browser.

Available Nodes

NodeInputOutputDescription
TRELLIS Image to 3DImage3D Model (GLB)Convert a single image to 3D
TRELLIS Text to 3DText prompt3D Model (GLB)Generate 3D from description
TRELLIS Multi-ViewMultiple images3D Model (GLB)Use multiple views for better quality
TRELLIS Export3D ModelFileExport to various formats

Method 4: Docker Installation

Docker provides a reproducible environment that works across platforms.

Step 1: Install Docker

# Ubuntu
sudo apt install docker.io docker-compose -y
sudo usermod -aG docker $USER

# Start Docker
sudo systemctl start docker
sudo systemctl enable docker

Step 2: Build the Docker Image

git clone https://github.com/microsoft/TRELLIS.2.git
cd TRELLIS.2

# Build the image (includes CUDA support)
docker build -t trellis2 .

Step 3: Run the Container

# Run with GPU support
docker run --gpus all -p 7860:7860 -v ./outputs:/app/outputs trellis2

Access the web interface at http://localhost:7860.

Configuration Options

After installation, you can configure TRELLIS 2 through a config file or command-line arguments.

Config File (config.yaml)

model:
  name: "trellis2-4b"
  weights_path: "./weights/"

generation:
  default_resolution: 512
  default_sampling_steps: 12
  default_guidance_scale: 7.5

server:
  host: "0.0.0.0"
  port: 7860
  max_batch_size: 4

output:
  default_format: "glb"
  save_intermediates: false

Command-Line Arguments

python infer.py \
  --image_path input.png \
  --output_path output.glb \
  --resolution 1024 \
  --sampling_steps 25 \
  --guidance_scale 10.0 \
  --seed 42

Troubleshooting Common Issues

CUDA Out of Memory

Symptom: RuntimeError: CUDA out of memory

Solutions:

  1. Reduce resolution: --resolution 256 or --resolution 512
  2. Reduce sampling steps: --sampling_steps 4
  3. Close other GPU-intensive applications
  4. Use the online platform for high-resolution generation

Python Version Issues

Symptom: ModuleNotFoundError or syntax errors

Solution: Ensure Python 3.10 or 3.11 is being used:

python --version  # Should be 3.10.x or 3.11.x

CUDA Version Mismatch

Symptom: RuntimeError: CUDA version mismatch

Solution: Reinstall PyTorch matching your CUDA version:

# For CUDA 11.8
pip install torch torchvision --index-url https://download.pytorch.org/whl/cu118

# For CUDA 12.1
pip install torch torchvision --index-url https://download.pytorch.org/whl/cu121

Model Weights Download Failure

Symptom: Download timeout or corrupted files

Solution: Download weights manually from Hugging Face:

# Using huggingface-cli
pip install huggingface-hub
huggingface-cli download microsoft/TRELLIS.2-4B --local-dir ./weights/

Slow Generation on Windows

Symptom: Generation takes much longer than expected

Solutions:

  1. Ensure CUDA is properly installed (nvidia-smi should work)
  2. Check that PyTorch is using GPU: python -c "import torch; print(torch.cuda.is_available())"
  3. Disable Windows GPU scheduling: Settings → System → Display → Graphics → Change default graphics settings

Performance Benchmarks

Expected generation times by GPU (512 resolution, 12 sampling steps):

GPUGeneration TimeVRAM Usage
RTX 4090~2.5s~6 GB
RTX 4080~3s~7 GB
RTX 3090~4s~8 GB
RTX 3080~5s~8 GB
RTX 4070~4s~6 GB
RTX 3060~8s~8 GB
GTX 1080 Ti~12s~8 GB
A100~2s~6 GB

Updating TRELLIS 2

To update to the latest version:

cd TRELLIS.2

# Pull latest changes
git pull origin main

# Update dependencies
pip install -r requirements.txt

# Download new weights if available
python download_weights.py

Alternatives to Local Installation

If your hardware doesn't meet the requirements or you prefer not to install locally:

Use TRELLIS 2 Online — No GPU Required

FeatureLocalOnline Platform
Setup time15-60 min0 min
GPU neededYes (NVIDIA)No
Max resolutionGPU-dependentUp to 1536³
Batch processingYesYes
CostHardware + electricityFree tier available
UpdatesManualAutomatic

Next Steps

After installation, learn how to use TRELLIS 2 effectively:

  • How to Use TRELLIS 2: complete usage guide with parameter tuning
  • How to Test TRELLIS 2: evaluate output quality with benchmarks
  • What is TRELLIS 3D?: understand the technology behind the model

Related articles:

  • How to Use TRELLIS 2: complete usage guide
  • What is TRELLIS 3D?: learn about the AI model
  • How to Turn an Image into a 3D Model: broader guide covering multiple methods
All Posts

Author

avatar for Trellis2 Team
Trellis2 Team

3D technology specialists focused on AI-powered 3D model generation, format conversion, and browser-based 3D rendering. We test and review 3D tools so you don't have to.

Categories

    System RequirementsMinimum RequirementsGPU CompatibilityInstallation MethodsMethod 1: Linux InstallationStep 1: Install PrerequisitesStep 2: Clone the RepositoryStep 3: Create Virtual EnvironmentStep 4: Install DependenciesStep 5: Download Model WeightsStep 6: Verify InstallationMethod 2: Windows InstallationOption A: One-Click Installer (Recommended for Beginners)Option B: Manual InstallationStep 1: Install PrerequisitesStep 2: Clone and Set UpStep 3: Install DependenciesStep 4: Download Weights and TestMethod 3: ComfyUI IntegrationStep 1: Install ComfyUIStep 2: Install TRELLIS 2 Custom NodesStep 3: Download Model WeightsStep 4: Start ComfyUIAvailable NodesMethod 4: Docker InstallationStep 1: Install DockerStep 2: Build the Docker ImageStep 3: Run the ContainerConfiguration OptionsConfig File (config.yaml)Command-Line ArgumentsTroubleshooting Common IssuesCUDA Out of MemoryPython Version IssuesCUDA Version MismatchModel Weights Download FailureSlow Generation on WindowsPerformance BenchmarksUpdating TRELLIS 2Alternatives to Local InstallationNext Steps

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