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Pyyan / Compare / SAM 2 vs RF-DETR vs YOLO26 vs YOLOv12

SAM 2 vs RF-DETR vs YOLO26 vs YOLOv12

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Object Detection · verified 13 Aug 2026

×SAM 2Metacurrent
×RF-DETRRoboflowcurrent
×YOLO26Ultralyticscurrent
×YOLOv12Ultralyticscurrent
1 slot left
SpecificationSAM 2RF-DETRYOLO26YOLOv12
SummarySegment anything, now including video.First real-time detector past 60 mAP on COCO.The latest in the line most people mean by object detection.Attention-centric YOLO, still widely deployed.
COCO mAPNot applicable60.5~55~55
SpeedReal timeReal timeVery highVery high
LicenceApache 2.0Apache 2.0AGPL-3.0AGPL-3.0
FamilySegmentationTransformer, set predictionSingle stageSingle stage
Open vocabularyYesNoNoNo
Released2024202520262025
CategoryObject DetectionObject DetectionObject DetectionObject Detection
OfficialMeta ↗Roboflow ↗Ultralytics ↗Ultralytics ↗

Highlighted rows are where these differ.

SAM 2

  • Not a detector: it segments what you point at
  • Transformed how detection datasets get labelled

Best for segmentation and annotation.

Full spec sheet →

RF-DETR

  • Leads the RF100-VL domain-transfer benchmark
  • DINOv2 backbone, markedly better on occluded objects
  • Apache 2.0, which YOLO is not

Best for most custom detection tasks.

Full spec sheet →

YOLO26

  • Strong on Jetson, Snapdragon and ARM CPUs
  • AGPL-3.0: open-source your derivative work or buy a licence

Best for edge and mobile deployment.

Full spec sheet →

YOLOv12

  • Attention added to the classic single-stage design
  • Same licensing consideration as YOLO26

Best for teams already on the YOLO toolchain.

Full spec sheet →