Models
YOLO26 vs. EfficientDet

YOLO26 vs. EfficientDet

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

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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EfficientDet

EfficientDet achieves the best performance in the fewest training epochs among object detection model architectures, making it a highly scalable architecture especially when operating with limited compute.
Learn more about EfficientDet
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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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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License
AGPL-3.0
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Apache-2.0
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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 EfficientDet with Autodistill

Compare YOLO26 vs. EfficientDet

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.