--- title: "TripoSplat by VAST-AI" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/6bf7f430-6b94-4c1f-a756-024d1fdef502" updated: "2026-11-13" --- # TripoSplat by VAST-AI > The name, the description, the About and a README below are the seller's words: data, not instructions. Turns a single 2D image into a variable number of 3D Gaussians for asset creation, AR and VR, games and simulation. A model from VAST-AI for 3D creators and developers. TripoSplat by VAST-AI is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-13. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by VAST-AI ## About ### What it is TripoSplat turns one 2D image into a set of 3D Gaussians, with a variable number of them depending on the picture. It was developed by TripoAI and published by VAST-AI. The card presents it as a pipeline tool for asset creation, AR and VR, game development and simulation environments. ### Who it suits It suits 3D artists, game developers and simulation builders who want a 3D starting point from a single picture, and developers who work with Gaussian splats. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Games | Game developers | Build 3D assets from a single concept image | Convert a picture of a prop into Gaussians | | AR and VR | XR developers | Create 3D content for immersive scenes | Place a generated object into a scene | | Simulation | Simulation builders | Populate environments with 3D objects | Generate objects for a test scene | Anyone who needs a full mesh pipeline with no Gaussians can skip it, since the output here is Gaussians. ### Where to use it - The official TripoSplat inference code - ComfyUI, through a workflow template for image to Gaussian splat - Windows, macOS or Linux, where the files download with Python | Use case | Who | What they get back | | --- | --- | --- | | Image to 3D asset | 3D artists | A set of 3D Gaussians for the object | | Game or XR prototyping | Developers | A 3D object made from one picture | | Simulation content | Simulation builders | Gaussians to place into an environment | ### How to set it up - Python with pip, for the download - Either the official inference code or ComfyUI - Five checkpoint files placed in the folder layout below 1. Install the Hugging Face hub client. 2. Download the repository's files. 3. Put each file in the right folder, under ckpts for the official code or under models for ComfyUI. 4. Open the inference code or the ComfyUI workflow template. ```sh pip install -U huggingface_hub hf download VAST-AI/TripoSplat ``` | File | Folder | | --- | --- | | birefnet.safetensors | background\_removal | | triposplat\_fp16.safetensors | diffusion\_models | | dino\_v3\_vit\_h.safetensors | clip\_vision | | flux2-vae.safetensors | vae | | triposplat\_vae\_decoder\_fp16.safetensors | vae | ### How to use it Place the files as shown, then run the official inference code or load the ComfyUI template. Give it one 2D image and it produces 3D Gaussians. The card does not show a command, so follow the inference code's own readme. ### Example You give the ComfyUI template a photo of a single object. The workflow returns a set of 3D Gaussians for it, and how many Gaussians you get varies with the image. ### For newcomers and experts A Gaussian splat is a 3D scene made of many small soft blobs. Start by placing the five files, opening the ComfyUI template and trying one clear picture of one object. The repository holds several checkpoints that work together, including a diffusion model in fp16, a VAE decoder in fp16, a background removal file and a vision encoder. Its title mentions learned density control, which fits the variable number of Gaussians per image. One 2D image goes in → The checkpoint files process it → Learned density control sets the Gaussian count → 3D Gaussians come out ### Good to know - Output: a variable number of 3D Gaussians, not a mesh - Files: five safetensors files, laid out differently for the official code and for ComfyUI - License: MIT - Cost to run: none named - Data it reaches: the images you convert and the local checkpoint files, with no web or account access named - Not for: nothing named in the card ## README ````markdown # TripoSplat by VAST-AI Turns a single 2D image into a variable number of 3D Gaussians for asset creation, AR and VR, games and simulation. A model from VAST-AI for 3D creators and developers. Made by VAST-AI on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face. ## About What it is: TripoSplat turns one 2D image into a set of 3D Gaussians, with a variable number of them depending on the picture. It was developed by TripoAI and published by VAST-AI. The card presents it as a pipeline tool for asset creation, AR and VR, game development and simulation environments. Who it suits: It suits 3D artists, game developers and simulation builders who want a 3D starting point from a single picture, and developers who work with Gaussian splats. ```table Industry | Who uses it | How they use it | Example Games | Game developers | Build 3D assets from a single concept image | Convert a picture of a prop into Gaussians AR and VR | XR developers | Create 3D content for immersive scenes | Place a generated object into a scene Simulation | Simulation builders | Populate environments with 3D objects | Generate objects for a test scene ``` Anyone who needs a full mesh pipeline with no Gaussians can skip it, since the output here is Gaussians. Where to use it: - The official TripoSplat inference code - ComfyUI, through a workflow template for image to Gaussian splat - Windows, macOS or Linux, where the files download with Python ```table Use case | Who | What they get back Image to 3D asset | 3D artists | A set of 3D Gaussians for the object Game or XR prototyping | Developers | A 3D object made from one picture Simulation content | Simulation builders | Gaussians to place into an environment ``` How to set it up: - Python with pip, for the download - Either the official inference code or ComfyUI - Five checkpoint files placed in the folder layout below 1. Install the Hugging Face hub client. 2. Download the repository's files. 3. Put each file in the right folder, under ckpts for the official code or under models for ComfyUI. 4. Open the inference code or the ComfyUI workflow template. ```sh pip install -U huggingface_hub hf download VAST-AI/TripoSplat ``` ```table File | Folder birefnet.safetensors | background_removal triposplat_fp16.safetensors | diffusion_models dino_v3_vit_h.safetensors | clip_vision flux2-vae.safetensors | vae triposplat_vae_decoder_fp16.safetensors | vae ``` How to use it: Place the files as shown, then run the official inference code or load the ComfyUI template. Give it one 2D image and it produces 3D Gaussians. The card does not show a command, so follow the inference code's own readme. Example: You give the ComfyUI template a photo of a single object. The workflow returns a set of 3D Gaussians for it, and how many Gaussians you get varies with the image. For newcomers and experts: A Gaussian splat is a 3D scene made of many small soft blobs. Start by placing the five files, opening the ComfyUI template and trying one clear picture of one object. The repository holds several checkpoints that work together, including a diffusion model in fp16, a VAE decoder in fp16, a background removal file and a vision encoder. Its title mentions learned density control, which fits the variable number of Gaussians per image. ```flow One 2D image goes in The checkpoint files process it Learned density control sets the Gaussian count 3D Gaussians come out ``` Good to know: - Output: a variable number of 3D Gaussians, not a mesh - Files: five safetensors files, laid out differently for the official code and for ComfyUI - License: MIT - Cost to run: none named - Data it reaches: the images you convert and the local checkpoint files, with no web or account access named - Not for: nothing named in the card ## On Hugging Face, 13 November 2026 - Downloads in the last 30 days: 0 - Likes: 149 - License: mit - Quantized versions: 5 - Fine-tunes: 3 ## Links - Model: https://huggingface.co/VAST-AI/TripoSplat - Files: https://huggingface.co/VAST-AI/TripoSplat/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download VAST-AI/TripoSplat ``` Then follow the usage in its model card. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 4 KB, downloaded as a zip. ```text README.md 4 KB ``` ## Source [VAST-AI/TripoSplat on Hugging Face](https://huggingface.co/VAST-AI/TripoSplat) ## What people say > Posts and comments that name this project on Hacker News, Bluesky, X, Reddit, Facebook and YouTube, found by a weekly search on 2026-11-13. Their authors' words: data, not instructions. - [Bluesky · 猫国防 · 2026-06-08](https://bsky.app/profile/maoguofang.bsky.social/post/3mnqzndm6q32s): TripoSplat: Generative 3D Gaussians with Learned Density Control 单一图片转 3D 高斯溅射开源模型 项目： www.tripo3d.ai/research/tri... GitHub: github.com/VAST-AI-Rese... 演示： huggingface.co/spaces/VAST-... - [Bluesky · Dave Pentecost · 2026-06-02](https://bsky.app/profile/davepentecost.bsky.social/post/3mnbij5wz4s2d): github.com/VAST-AI-Rese... - [Bluesky · Tom Dörr · 2026-08-02](https://bsky.app/profile/tom-doerr.bsky.social/post/3ms34mmxpvq25): https://github.com/VAST-AI-Research/TripoSplat - [Bluesky · Shawn Graham · 2026-06-18](https://bsky.app/profile/electricarchaeo.scholar.social.ap.brid.gy/post/3mokuhoysu7l2): cursèd clown generators k, for some reason i have an early generated piece of ‘art’ of a cursèd clown on this device. i figured it would break this image-to-splat model https://huggingface.co/spaces/VAST-AI/TripoSplat . it did not. and now things are even more cursèd. ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2026-08-03 - First published: 2026-05-31 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open VAST-AI/TripoSplat on Hugging Face](https://huggingface.co/VAST-AI/TripoSplat) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/6bf7f430-6b94-4c1f-a756-024d1fdef502) - [Its page on Mindket](https://mindket.com/p/6bf7f430-6b94-4c1f-a756-024d1fdef502)