Models
YOLO26 vs. SegFormer

YOLO26 vs. SegFormer

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

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.
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SegFormer

SegFormer is a computer vision framework used in semantic segmentation tasks, implemented with transformers.
Model Type
Object Detection
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Semantic Segmentation
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Model Features
Item 1 Info
Item 2 Info
Architecture
YOLO
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Transformers
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Annotation Format
Instance Segmentation
Instance Segmentation
Framework
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PyTorch
GitHub Stars
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2.2k+
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License
AGPL-3.0
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NVIDIA Source Code
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Training Notebook

Compare YOLO26 and SegFormer with Autodistill

Compare YOLO26 vs. SegFormer

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.