Models
YOLO26 vs. YOLOv3 Keras

YOLO26 vs. YOLOv3 Keras

Both YOLO26 and YOLOv3 Keras are commonly used in computer vision projects. Below, we compare and contrast YOLO26 and YOLOv3 Keras.

Models

icon-model

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
icon-model

YOLOv3 Keras

Though it is no longer the most accurate object detection algorithm, YOLO v3 is still a very good choice when you need real-time detection while maintaining excellent accuracy. Keras implementation.
Learn more about YOLOv3 Keras
Model Type
Object Detection
--
Object Detection
--
Model Features
Item 1 Info
Item 2 Info
Architecture
YOLO
--
YOLO
--
Annotation Format
Instance Segmentation
Instance Segmentation
Framework
--
--
Keras
GitHub
--
View Repo
--
View Repo
GitHub Stars
--
7.1k+
--
License
AGPL-3.0
--
MIT
--
Paper
--
View Paper
--
View Paper
Training Notebook
Train on Colab
--
Train on Colab
--
Deploy Model
--
rocket icon
Deploy with Roboflow
--
rocket icon
Deploy with Roboflow
Compare Alternatives
--
Compare with...
--
Compare with...

Compare YOLO26 and YOLOv3 Keras with Autodistill

Compare YOLO26 vs. YOLOv3 Keras

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.