BiRefNet Massive (birefnet-massive) background removal#
BiRefNet checkpoint trained on a large mix of segmentation datasets.
Run it: rembg i -m birefnet-massive input.jpg output.png setup
birefnet-massive results on 34 images
Original, cutout and alpha matte for every Bench v0 image, with its MAE and MGE against the ground truth. Each opens the side-by-side comparison.
People (12)




































Plants (7)





















Objects with Details (6)
Motion (5)
animal (2)
Film Camera (2)
How to run birefnet-massive
birefnet-massive ships with rembg as the session birefnet-massive. The weights download on first use.
Command line
pip install "rembg[cpu,cli]"
rembg i -m birefnet-massive input.jpg output.pngPython
from rembg import new_session, remove
from PIL import Image
session = new_session("birefnet-massive") # load once, reuse for every image
output = remove(Image.open("input.jpg"), session=session)
output.save("output.png")Other sessions: all rembg models.
BiRefNet Massive as a free, open-source remove.bg alternative
remove.bg is a paid cloud service. BiRefNet Massive is open weights under MIT, so commercial use is allowed. It runs on your own machine (rembg i -m birefnet-massive input.jpg output.png), offline, with no upload and no per-image cost. On Bench v0 it ranks #7 of 17 by accuracy (MAE); withoutBG Open Weights ranks #3.
remove.bg is not in Bench v0, so there is no score against it. See withoutBG Open Weights and remove.bg side by side, or compare all remove.bg alternatives.
Quick take
- Best for: General cutouts; an alternative to birefnet-general on mixed content
- Avoid when: Strict latency or memory budgets
- Notes: Same size and speed as birefnet-general; compare both on your images.
When a hosted model is worth it
birefnet-massive is free and runs on your machine; keep it if the results above are good enough. If you need finer hair and edges, or don't want to run large models locally, rembg also ships the withoutBG Pro Model as the withoutbg session, ranked #1 of 17 by accuracy on Bench v0. Images are sent to withoutBG's servers.
Same command, hosted model
export WITHOUTBG_API_KEY=sk_...
rembg i -m withoutbg input.jpg output.pngSign up for 50 free credits (no credit card) or See its results.












































