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Pyyan / Compare / OWLv2 vs RF-DETR vs YOLOv12

OWLv2 vs RF-DETR vs YOLOv12

3 of 5

Object Detection · verified 13 Aug 2026

×OWLv2Googlecurrent
×RF-DETRRoboflowcurrent
×YOLOv12Ultralyticscurrent
2 slots left
SpecificationOWLv2RF-DETRYOLOv12
SummaryOpen-vocabulary detection trained with self-labelling.First real-time detector past 60 mAP on COCO.Attention-centric YOLO, still widely deployed.
COCO mAP~45 zero-shot60.5~55
SpeedModerateReal timeVery high
LicenceApache 2.0Apache 2.0AGPL-3.0
FamilyOpen vocabularyTransformer, set predictionSingle stage
Open vocabularyYesNoNo
Released202320252025
CategoryObject DetectionObject DetectionObject Detection
OfficialGoogle ↗Roboflow ↗Ultralytics ↗

Highlighted rows are where these differ.

OWLv2

  • Accepts an image as the query, not just text

Best for querying by example image.

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 →

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 →