Virtual try-on

FitDiT

Tencent's transformer-based try-on: more accurately reproduces fabric texture, fine prints and garment length. Non-commercial license.

Developer
Tencent and Fudan University, China
First release
Dec 2024
Latest release
Dec 2024
Sizes
based on SD3
License
Non-commercial onlyCC BY-NC-SA 4.0 (non-commercial use only)
Running
On your own serverNeeds a GPU
Industries
Retail and marketplaces
Deploy on your server Hugging Face GitHub

What it does

  • Try-on of items with complex prints and textures
  • Test product cards on a model
  • Checking length and fit on a photo

Where it is used

Online apparel retailMarketplacesFashion brands

Hardware requirements

LaptopLaptop or regular PC, up to 8 GB of VRAM — smaller versions
no versions
1 GPUOne GPU with 16–80 GB — mid-size versions
fits
ClusterServer with several GPUs — flagship versions
no versions

Versions

  1. FitDiT

How to run it

On your own serverWeights are downloaded from Hugging Face and served with vLLM (load and API) or llama.cpp (modest hardware). The model then runs in a closed network with no per-request fees.Hugging Face
How much hardware you needCalculate the VRAM for the model size, context length and number of concurrent requests.Open the hardware calculator

I can set this up end to end: pick the model size, deploy it on your server and connect it to your systems.

Frequently asked questions

Can FitDiT be used in a commercial project?

No. License: CC BY-NC-SA 4.0 (non-commercial use only). A commercial product needs a different model or a separate agreement with the rights holder.

What hardware does FitDiT need?

At minimum: One GPU with 16–80 GB — mid-size versions. Without a GPU the model is not practical. You can calculate the exact VRAM for your model size and context in the hardware calculator.

Does FitDiT support Russian?

Language does not matter for this model: it does not work with text.

Where can I download FitDiT and what does it cost?

The FitDiT weights are open and free to download. You only pay for the hardware it runs on and for the setup. Source links are at the bottom of this page.

How I deploy it for clients

  1. SelectionI pick the model size for your task and hardware and test it on your examples.
  2. DeploymentI deploy it on your server or in a closed network and provide an API.
  3. Fine-tuningI fine-tune it on your data (LoRA) or connect a knowledge base — whichever is cheaper for the task.
  4. IntegrationI connect it to your CRM, ERP, bot, website or team chat and set up monitoring.

Similar models

Virtual try-onIDM-VTONKAIST and OMNIOUS.AI · South KoreaNon-commercial only

One of the best-known open virtual try-on models: moves a garment from a product photo onto a photo of a person, keeping prints and logos well. Non-commercial license.

DetailsVirtual try-onLeffaMeta AI (with King's College London) · USACommercial use with conditions

Meta's model for virtual try-on and changing a person's pose in a photo. Carefully transfers fine fabric details and lettering. MIT license, but the training data is non-commercial.

DetailsVirtual try-onFASHN VTONFASHN AI · IsraelCommercial use allowed

A rare open try-on model with a commercial license: mask-free, accepts a photo of the item on a model or a flat lay. Weights are about 2 GB.

Details

Source: github.com/BoyuanJiang/FitDiT. Data checked against the model card on 22 Sep 2026. Have a lawyer review the license before commercial launch.