PartCrafter vs Stable Fast 3D

PartCrafter is a free, open-source model that generates multiple 3D parts and objects from a single RGB image. It can handle individual objects and complex scenes, producing distinct meshes with meaningful part structure without requiring a pre-segmented image. Its architecture represents parts with disentangled latent tokens and uses hierarchical attention to pass information within and across parts. Local inference scripts can remove backgrounds and optionally apply style transfer to adapt real-world photos toward the rendered-image domain used for training. An optional vision-language feature can suggest the number of parts; Gemini is the default provider, and the provider architecture can be extended. Pretrained object-level and scene-level weights are hosted on Hugging Face. Installation is from the GitHub repository in a Python environment, and inference requires a CUDA-enabled GPU with at least 8 GB of VRAM. The linked Hugging Face demo is paused, though its page says users can ask the authors to restart it. The repository lists an MIT license and provides the software as-is, without warranty.

Stable Fast 3D turns an image of an object into a textured, UV-unwrapped 3D mesh. Stability AI describes the model as generating a 3D model from one image in under one second. It expects a 512 × 512 pixel input, applies a delighting step, and predicts roughness and metallic material parameters. The official code example saves the result as a GLB file. The repository includes custom nodes and an example workflow for ComfyUI, and API access is available. Documented inference options include CUDA, CPU, and experimental Mac MPS; Windows support is marked experimental. Default settings use about 6 GB of VRAM for one image. Stability AI identifies game and VR developers and professionals in retail, architecture, and design among its intended users. The Community License is free; commercial use above US $1 million in annual revenue requires an Enterprise License. Access to model files requires agreeing to share contact information and accepting the license.