Models
YOLO26 vs. YOLOv3 PyTorch

YOLO26 vs. YOLOv3 PyTorch

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

Models

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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
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YOLOv3 PyTorch

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. PyTorch version.
Learn more about YOLOv3 PyTorch
Model Type
Object Detection
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Object Detection
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Model Features
Item 1 Info
Item 2 Info
Architecture
YOLO
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YOLO
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Annotation Format
Instance Segmentation
Instance Segmentation
Framework
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PyTorch
GitHub
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View Repo
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View Repo
GitHub Stars
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7.2k+
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License
AGPL-3.0
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GPL-3.0
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Paper
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View Paper
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View Paper
Training Notebook
Train on Colab
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Train on Colab
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Deploy Model
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Deploy with Roboflow
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Deploy with Roboflow
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Compare YOLO26 and YOLOv3 PyTorch with Autodistill

Compare YOLO26 vs. YOLOv3 PyTorch

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.