YOLO26 vs. Faster R-CNN: Compared and Contrasted

Models

YOLO26

YOLO26 is a real-time, NMS-free YOLO model optimized for edge deployment, supporting multiple vision tasks across scalable model sizes.

Learn more about YOLO26

Faster R-CNN

One of the most accurate object detection algorithms but requires a lot of power at inference time. A good choice if you can do processing asynchronously on a server.

Learn more about Faster R-CNN

Model Type

Object Detection

Model Features

Item 1 Info

Item 2 Info

Architecture

YOLO

Annotation Format

Instance Segmentation

Framework

TensorFlow 1.5

GitHub

View Repo

GitHub Stars

7.5k+

License

AGPL-3.0

MIT

Paper

View Paper

Training Notebook

Train on Colab

Deploy Model

Deploy with Roboflow

Compare YOLO26 vs. Faster R-CNN

Provide your own image below to test YOLOv8 and YOLOv9 model checkpoints trained on the Microsoft COCO dataset.

COCO can detect 80 common objects, including cats, cell phones, and cars.

YOLO26 vs. Faster R-CNN

Models

YOLO26

Faster R-CNN

Compare YOLO26 and Faster R-CNN with Autodistill

Compare YOLO26 vs. Faster R-CNN