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

Grounding DINO vs RF-DETR vs YOLOv12 vs RTMDet

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Object Detection · verified 13 Aug 2026

×IGrounding DINOIDEA Researchcurrent
×RF-DETRRoboflowcurrent
×YOLOv12Ultralyticscurrent
×RTMDetOpenMMLabcurrent
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SpecificationGrounding DINORF-DETRYOLOv12RTMDet
SummaryDetects whatever you describe in words.First real-time detector past 60 mAP on COCO.Attention-centric YOLO, still widely deployed.Pure throughput, and an MIT licence.
COCO mAP~52 zero-shot60.5~55~52
SpeedModerateReal timeVery high300+
LicenceApache 2.0Apache 2.0AGPL-3.0MIT
FamilyOpen vocabularyTransformer, set predictionSingle stageSingle stage
Open vocabularyYesNoNoNo
Released2023202520252022
CategoryObject DetectionObject DetectionObject DetectionObject Detection
OfficialIDEA ResearchRoboflowUltralyticsOpenMMLab

Highlighted rows are where these differ.

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 →

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 →