Models
YOLOv11 vs. YOLOv3 PyTorch

YOLOv11 vs. YOLOv3 PyTorch

Both YOLO11 and YOLOv3 PyTorch are commonly used in computer vision projects. Below, we compare and contrast YOLO11 and YOLOv3 PyTorch.

Models

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YOLO11

YOLO11 is a computer vision model that you can use for object detection, segmentation, and classification.
Learn more about YOLO11
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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
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YOLO
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Frameworks
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PyTorch
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Annotation Format
Instance Segmentation
Instance Segmentation
GitHub
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View Repo
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View Repo
GitHub Stars
29000
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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 YOLO11 and YOLOv3 PyTorch with Autodistill

Compare YOLOv11 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.