Pyyan / Compare / DETR vs RF-DETR vs YOLOv12 vs RTMDet

DETR vs RF-DETR vs YOLOv12 vs RTMDet

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Object Detection · verified 13 Aug 2026

×DETRMetacurrent
×RF-DETRRoboflowcurrent
×YOLOv12Ultralyticscurrent
×RTMDetOpenMMLabcurrent
1 slot left
SpecificationDETRRF-DETRYOLOv12RTMDet
SummaryThe paper that removed anchors and NMS.First real-time detector past 60 mAP on COCO.Attention-centric YOLO, still widely deployed.Pure throughput, and an MIT licence.
COCO mAP~4460.5~55~52
SpeedLowReal timeVery high300+
LicenceApache 2.0Apache 2.0AGPL-3.0MIT
FamilyTransformer, set predictionTransformer, set predictionSingle stageSingle stage
Open vocabularyNoNoNoNo
Released2020202520252022
CategoryObject DetectionObject DetectionObject DetectionObject Detection
OfficialMetaRoboflowUltralyticsOpenMMLab

Highlighted rows are where these differ.

DETR

  • Reframed detection as set prediction
  • Slow to train, and every transformer detector descends from it

Best for understanding where RF-DETR came from.

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 →

RTMDet

  • Wins on raw speed where accuracy is sufficient
  • MIT, so no derivative-work obligation

Best for high frame-rate video.

Full spec sheet →