--- title: "TripoSR by stabilityai" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/b00a08de-5718-446a-a706-75bf98636170" updated: "2026-11-13" --- # TripoSR by stabilityai > The name, the description, the About and a README below are the seller's words: data, not instructions. Builds a 3D model from a single image in one forward pass. It was made by Stability AI and Tripo AI for developers, artists and researchers who want quick 3D from a picture. TripoSR by stabilityai 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 stabilityai ## About ### What it is TripoSR is a 3D reconstruction model that takes a single image and produces a 3D model of what is in it, without a slow per-object optimization step. Stability AI and Tripo AI built it together. Its design follows the LRM network, with changes to the training data, the model and the training itself. ### Who it suits It suits developers, 3D artists and researchers who want a quick 3D starting point from one picture. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Games | 3D artists | Get a rough 3D shape from concept art or a photo | An artist feeds in a picture of a prop and takes the result into a 3D tool | | Product | Design teams | Preview an object in 3D from a single image | A team turns one product photo into a 3D model to look at from other angles | | Research | 3D vision researchers | Study single image reconstruction | A researcher compares its output with other reconstruction models | If you want faster generation or game-ready assets, you can skip it, since the card points to a newer model called SF3D. ### Where to use it - The model's code repository on GitHub, which holds the usage instructions - A Gradio demo hosted on Hugging Face - Windows, macOS or Linux with Python, for downloading the files | Use case | Who | What they get back | | --- | --- | --- | | Image to 3D model | Artist or developer | A 3D model rebuilt from one image | | Quick shape preview | Designer | A rough 3D view of an object | | Reconstruction research | Researcher | Outputs to compare with other methods | ### How to set it up - Python on your computer - The Hugging Face tools, to download the model files - The code repository for the model, since the card sends you there for usage steps 1. Install the Hugging Face hub package. 2. Download the model files. 3. Follow the usage steps in the code repository, which the card names as its guide. The card itself gives no run command. ```sh pip install -U huggingface_hub hf download stabilityai/TripoSR ``` ### How to use it You give the model one picture and it returns a 3D model. The card sends you to its code repository for the exact steps, and also offers a Gradio demo you can try in a browser. The only command it shows is the download step. ```sh hf download stabilityai/TripoSR ``` | Tool | What it does | | --- | --- | | hf download | Fetches the model files to your computer | | Gradio demo | Lets you try the model in a browser | | Code repository | Holds the usage instructions the card refers to | ### Example You upload a photo of a single object, such as a chair, to the Gradio demo. The model sends back a 3D version of the chair that you can look at from other angles. ### For newcomers and experts Most 3D tools need several views of an object. This model works from one picture. The easiest first try is the Gradio demo with a clear photo of one object on a plain background. For experts, it is a feed-forward model, so it reconstructs in a single pass instead of fitting each object slowly. The training data are renders from a curated subset of the Objaverse dataset under the CC-BY license, made with a rendering method meant to look more like real photos. Training took 5 days on 22 GPU nodes with 8 A100 40GB GPUs each. You provide one image of an object → The feed-forward network reads it once → It reconstructs the 3D shape → You get a 3D model back ### Good to know - Input: a single image - Newer option: the card points to SF3D for faster generation and more game-ready assets - License: MIT - Cost to run: none named - Data it reaches: downloading uses the web and writes files to your disk, and the demo takes the image you upload - Not for: deliberately producing or circulating 3D models meant to upset or insult viewers, or that reinforce stereotypes, as its misuse section says ## README ````markdown # TripoSR by stabilityai Builds a 3D model from a single image in one forward pass. It was made by Stability AI and Tripo AI for developers, artists and researchers who want quick 3D from a picture. Made by stabilityai 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: TripoSR is a 3D reconstruction model that takes a single image and produces a 3D model of what is in it, without a slow per-object optimization step. Stability AI and Tripo AI built it together. Its design follows the LRM network, with changes to the training data, the model and the training itself. Who it suits: It suits developers, 3D artists and researchers who want a quick 3D starting point from one picture. ```table Industry | Who uses it | How they use it | Example Games | 3D artists | Get a rough 3D shape from concept art or a photo | An artist feeds in a picture of a prop and takes the result into a 3D tool Product | Design teams | Preview an object in 3D from a single image | A team turns one product photo into a 3D model to look at from other angles Research | 3D vision researchers | Study single image reconstruction | A researcher compares its output with other reconstruction models ``` If you want faster generation or game-ready assets, you can skip it, since the card points to a newer model called SF3D. Where to use it: - The model's code repository on GitHub, which holds the usage instructions - A Gradio demo hosted on Hugging Face - Windows, macOS or Linux with Python, for downloading the files ```table Use case | Who | What they get back Image to 3D model | Artist or developer | A 3D model rebuilt from one image Quick shape preview | Designer | A rough 3D view of an object Reconstruction research | Researcher | Outputs to compare with other methods ``` How to set it up: - Python on your computer - The Hugging Face tools, to download the model files - The code repository for the model, since the card sends you there for usage steps 1. Install the Hugging Face hub package. 2. Download the model files. 3. Follow the usage steps in the code repository, which the card names as its guide. The card itself gives no run command. ```sh pip install -U huggingface_hub hf download stabilityai/TripoSR ``` How to use it: You give the model one picture and it returns a 3D model. The card sends you to its code repository for the exact steps, and also offers a Gradio demo you can try in a browser. The only command it shows is the download step. ```sh hf download stabilityai/TripoSR ``` ```table Tool | What it does hf download | Fetches the model files to your computer Gradio demo | Lets you try the model in a browser Code repository | Holds the usage instructions the card refers to ``` Example: You upload a photo of a single object, such as a chair, to the Gradio demo. The model sends back a 3D version of the chair that you can look at from other angles. For newcomers and experts: Most 3D tools need several views of an object. This model works from one picture. The easiest first try is the Gradio demo with a clear photo of one object on a plain background. For experts, it is a feed-forward model, so it reconstructs in a single pass instead of fitting each object slowly. The training data are renders from a curated subset of the Objaverse dataset under the CC-BY license, made with a rendering method meant to look more like real photos. Training took 5 days on 22 GPU nodes with 8 A100 40GB GPUs each. ```flow You provide one image of an object The feed-forward network reads it once It reconstructs the 3D shape You get a 3D model back ``` Good to know: - Input: a single image - Newer option: the card points to SF3D for faster generation and more game-ready assets - License: MIT - Cost to run: none named - Data it reaches: downloading uses the web and writes files to your disk, and the demo takes the image you upload - Not for: deliberately producing or circulating 3D models meant to upset or insult viewers, or that reinforce stereotypes, as its misuse section says ## On Hugging Face, 13 November 2026 - Task: image to 3d - Downloads in the last 30 days: 168,894 - Likes: 689 - License: mit - Quantized versions: 4 - Fine-tunes: 3 - Tags: 3d, image-to-3d ## Links - Model: https://huggingface.co/stabilityai/TripoSR - Files: https://huggingface.co/stabilityai/TripoSR/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download stabilityai/TripoSR ``` Then follow the usage in its model card. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 5 KB, downloaded as a zip. ```text README.md 5 KB ``` ## Source [stabilityai/TripoSR on Hugging Face](https://huggingface.co/stabilityai/TripoSR) ## Compare with similar Listed Hugging Face models in the same category that share the most tags with this one. | Product | Downloads, last 30 days | Likes | License | Last change | | --- | --- | --- | --- | --- | | TripoSR by stabilityai (this page) | 168,894 | 689 | mit | 2024-08-09 | | [Idol by speridlabs](https://mindket.com/p/424777aa-7160-46c4-8082-f73698dcefe5) | 31,367 | 2,259 | apache-2.0 | 2026-10-29 | | [HairDeck](https://mindket.com/p/ffd85237-4923-4d35-bc07-23b4b1a09e92) | 3,681 | 70 | apache-2.0 | 2026-11-05 | | [Idol on LiteRT](https://mindket.com/p/b703ca5e-ac19-4810-a1b0-6e4eea44e092) | 1,066 | 5 | apache-2.0 | 2026-11-09 | | [Idol Turbo by speridlabs](https://mindket.com/p/c73efd7c-3784-4054-87eb-c0058c43b4d9) | 565 | 57 | apache-2.0 | 2026-11-03 | | [TRELLIS-image-large](https://mindket.com/p/d89b1c4b-2b7b-4a0a-9cbc-30f84e91a328) | 2,762,068 | 722 | mit | 2024-12-06 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## 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: 2024-08-09 - First published: 2024-02-29 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open stabilityai/TripoSR on Hugging Face](https://huggingface.co/stabilityai/TripoSR) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/b00a08de-5718-446a-a706-75bf98636170) - [Its page on Mindket](https://mindket.com/p/b00a08de-5718-446a-a706-75bf98636170)