It's Idol, a new open-source image-to-3D model from Speridlabs, a small spatial AI lab. It turns a photo, a render or a generated image into a 3D Gaussian splat and saves it as a standard 3DGS .ply that opens in any splat viewer. What you get: Open weights and code: both Apache 2.0, about 3.1 GB of weights on Hugging Face plus an inference SDK on GitHub Low VRAM: 7.2 GB at peak, so mid-range NVIDIA cards can run it Background removal built in: it cuts out the object and frames it, with separate modes for photos and for renders or generated images Up to 1,048,576 Gaussians: 262,144 by default, and you can go lower for speed Their benchmark: against TripoSplat, TRELLIS and LGM it scored best on 6 of 7 quality metrics Already in other tools: community ComfyUI nodes and a LichtFeld Studio plugin appeared within two days About the "2 seconds" you might have seen: that's on top-end hardware. In their own table at default settings it takes 3.4 s on a B300, 14.1 s on an RTX 5090, 19.1 s on a 4090 and 46.2 s on a 3080. The output is a splat, not a mesh, so it won't drop into a game engine like a regular model. It also needs access to two gated models, Meta's DINOv3 and the FLUX.2-dev VAE, which come with their own terms. github: https://github.com/speridlabs/idol-sdk try it HF: https://huggingface.co/spaces/speridlabs/idol   submitted by   /u/Delicious-Shower8401   to   r/TopologyAI [link]   [comments]