metadata
license: mit
tags:
- image-to-3d
- trellis2
- quantized
- gptq
TRELLIS 2 Quantized (v3 GPTQ) — Standalone Package
Run TRELLIS 2 image-to-3D on consumer GPUs (RTX 3060 12GB / 8GB VRAM).
v3 GPTQ quantization: 7.5GB package instead of 16.2GB FP16. Zero quality loss on standard inputs (LPIPS 0.089 avg vs FP16 baseline).
Quick Start
pip install huggingface_hub
huggingface-cli download Lifec-321/trellis2-quantized-v3 --local-dir ./trellis2-quantized
python trellis2_quantized_inference.py --standalone-dir ./trellis2-quantized --image photo.png
Speed Modes
| Flag | GPU Required | Peak VRAM | Speed |
|---|---|---|---|
--low-vram (auto for GPUs with 12GB or less) |
8-12GB | ~4 GB | ~7 min |
--fast (auto for GPUs with 16GB or more) |
16-24GB | ~14 GB | ~6.5 min |
System Requirements
| Component | Minimum | Recommended |
|---|---|---|
| GPU VRAM | 8 GB | 12+ GB |
| System RAM | 16 GB | 32 GB |
| Disk | 15 GB free | 20 GB free |
| Python | 3.10+ | 3.10 |
| CUDA | 11.8+ | 12.1+ |