Hunyuan3D vs TripoSR

Hunyuan3D is Tencent’s system for generating 3D assets from text, images, or sketches. The international platform accepts up to four multi-view images, offers model editing and adjustment, and exports OBJ and GLB files. Its capabilities include text-to-3D, image-to-shape, and texture generation; Smart Topology supports triangular and quadrilateral faces. Tencent Cloud documents API tasks for generation, texturing, topology reduction, component generation, UV mapping, motion, auto-rigging, and format conversion. Hunyuan3D-2.1 releases full model weights and training code, and its repository documents a local Gradio app. A Blender add-on is listed for Hunyuan3D-2. The stated VRAM needs are 10 GB for shape generation, 21 GB for texture generation, and 29 GB for both. First-time API activation grants 100 credits, valid for one year. Paid packs include 1,000 credits for 100 CNY, paid once and 10,000 for 980 CNY, paid once; pay-as-you-go is billed at 0.12 yuan per credit, with monthly settlement.

TripoSR is a free, MIT-licensed open-source model that reconstructs a 3D object from one image. Tripo AI and Stability AI developed it collaboratively for researchers, developers, and creatives working in 3D generative AI and content creation. The project states that generation can take less than 0.5 seconds on an NVIDIA A100 GPU. Its repository provides command-line inference and a local Gradio app launched with Python. The app offers background removal, foreground-ratio and marching-cubes-resolution controls, and OBJ or GLB output. Inference accepts one or more image paths and can bake textures instead of vertex colors, with configurable texture resolution. Default settings use about 6 GB of VRAM for one image. Local setup lists Python 3.8 or newer, PyTorch, and requirements.txt dependencies; CUDA is optional when available. TripoSR supports image-to-3D and AI texturing, but not text-to-3D. Its listed platforms are Linux, self-hosted, and web.