Trellis 2
Trellis 2 AI 3D Model Generator Free Online
Trellis 2 launched on May 1, 2026 with 1 votes.
What it does
Trellis 2 is an AI 3D Generator for Text to 3D and Image to 3D, helping you create high-quality assets fast with preview and export.
Type a prompt or upload an image to generate polished models for products, characters, scenes, and concept work. Use an AI 3D Generator to turn text prompts and images into polished models with fast previews, cleaner iteration, and export. Use it to test your prompt and shape. For cleaner geometry, better textures, and production-ready output, upgrade and run Standard. Jump into dedicated 3D AI model pages for image-to-3D, text-to-3D, and production-ready asset workflows. Fast Tripo AI 3D generation for photo to 3D workflows, prototypes, AR scenes, and game asset drafts. Photo to 3D AI model drafts for object previews and cleanup planning. Image to 3D AI concepts with prompt direction and…from trellis2.art
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TRELLIS 3D AI2024 · trellis3d.co · ▲79Hi HN! I've built TRELLIS 3D AI, an open tool that converts 2D images into professional 3D assets using advanced AI technology. Technical Implementation: - Browser-based processing using WebGL - Structured LATents (SLAT) for maintaining geometric integrity - Dual output pipeline generating both GLB and 3D Gaussian formats - Real-time 3D preview using Three.js - Optimized for processing images up to 2048x2048px The core technology combines: - Pretrained vision encoders for image understanding - Rectified flow transformers for 3D geometry generation - Advanced neural networks for texture…
Run TRELLIS.2 Image-to-3D generation natively on Apple SiliconApr 2026 · github.com · ▲202I ported Microsoft's TRELLIS.2 (4B parameter image-to-3D model) to run on Apple Silicon via PyTorch MPS. The original requires CUDA with flash_attn, nvdiffrast, and custom sparse convolution kernels: none of which work on Mac. I replaced the CUDA-specific ops with pure-PyTorch alternatives: a gather-scatter sparse 3D convolution, SDPA attention for sparse transformers, and a Python-based mesh extraction replacing CUDA hashmap operations. Total changes are a few hundred lines across 9 files. Generates ~400K vertex meshes from single photos in about 3.5 minutes on M4 Pro (24GB). Not as fast as…




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