Photo editingComputer vision

BiRefNet

An open MIT-licensed model for precise object segmentation and background removal. RMBG-2.0 is built on it. Versions for 2K and for hair and semi-transparent edges.

Developer
Nankai University, China
First release
Mar 2024
Latest release
Jul 2025
Sizes
about 220M (lightweight lite versions available)
License
Commercial use allowedMIT
Ready-made builds
GGUF
Running
On your own serverAlso runs without a GPU
Industries
Retail and marketplaces, Marketing and content, Media and production
Deploy on your server Hugging Face GitHub

What it does

  • Bulk background removal from product photos
  • Precise masks for design and print
  • Cutting out people with hair for advertising

Where it is used

Online retail and marketplacesAdvertising and designPrinting

Hardware requirements

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

Versions

  1. BiRefNet dynamic matting
  2. BiRefNet dynamic
  3. BiRefNet HR (2K)
  4. BiRefNet matting
  5. BiRefNet lite
  6. BiRefNet

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. Quantization compresses a model so it takes less video memory and runs on more modest hardware. Answers change slightly, so quality is checked on your own examples.

Frequently asked questions

Can BiRefNet be used in a commercial project?

Yes. License: MIT. It allows commercial use, but it is still worth having a lawyer review the license before launch.

What hardware does BiRefNet need?

At minimum: Laptop or regular PC, up to 8 GB of VRAM — smaller versions. Some versions also run on an ordinary CPU, without a GPU. You can calculate the exact VRAM for your model size and context in the hardware calculator.

Does BiRefNet support Russian?

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

Where can I download BiRefNet and what does it cost?

The BiRefNet 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.

Comparisons

Similar models

Photo editingBRIA RMBGBRIA AI · IsraelNon-commercial only

BRIA's background removal, trained on licensed photos. Soft edges, hair, transparency. Video versions available. Business use requires a paid agreement.

DetailsPhoto editingBEN2Prama LLC · USACommercial use allowed

A background removal model focused on difficult edges: hair, fur, fine details. The open version is MIT-licensed and can process video.

DetailsPhoto editingInSPyReNet / transparent-backgroundTaehoon Kim (POSTECH) · South KoreaCommercial use allowed

A salient object detection model and the ready-made transparent-background tool built on it: removes backgrounds from photos, video and webcam with one command.

Details

Source: huggingface.co/api/models?author=ZhengPeng7. Data checked against the model card on 22 Sep 2026. Have a lawyer review the license before commercial launch.