PyyanThe AI Index

Pyyan / Compare / RF-DETR vs YOLO26 vs YOLOv12 vs Grounding DINO

RF-DETR vs YOLO26 vs YOLOv12 vs Grounding DINO

4 of 5

Object Detection · verified 13 Aug 2026

×RF-DETRRoboflowcurrent
×YOLO26Ultralyticscurrent
×YOLOv12Ultralyticscurrent
×IGrounding DINOIDEA Researchcurrent
1 slot left
SpecificationRF-DETRYOLO26YOLOv12Grounding DINO
SummaryFirst 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.Detects whatever you describe in words.
COCO mAP60.5~55~55~52 zero-shot
SpeedReal timeVery highVery highModerate
LicenceApache 2.0AGPL-3.0AGPL-3.0Apache 2.0
FamilyTransformer, set predictionSingle stageSingle stageOpen vocabulary
Open vocabularyNoNoNoYes
Released2025202620252023
CategoryObject DetectionObject DetectionObject DetectionObject Detection
OfficialRoboflow ↗Ultralytics ↗Ultralytics ↗IDEA Research ↗

Highlighted rows are where these differ.

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 →

Grounding DINO

  • Text prompt in, boxes out
  • Fine-tuning still beats it on specialised objects

Best for classes you have no data for.

Full spec sheet →