YOLOv9-E2E

yolov9-e2eIn LibreYOLO

LibreYOLO contributors · 2026

Code

Variants4

Parameters2.6M - 31.1M

Best Paper mAP-

LicenseMIT

Model Variants

All variants benchmarked on COCO val2017. Click any variant for the full hardware breakdown.

Model	Params	GFLOPs	Paper mAP	Best FPS
YOLOv9-E2E-T	2.6M	Unknown	-	-	Details
YOLOv9-E2E-S	8.7M	Unknown	-	-	Details
YOLOv9-E2E-M	24.7M	Unknown	-	-	Details
YOLOv9-E2E-C	31.1M	Unknown	-	-	Details

Architecture

Type

one-stage

Backbone

GELAN

Neck

PAN

Head

One-to-one head

anchor-freenms-freeTrained on COCO train2017

Run any model with one line

LibreYOLO has the best catalogue of state-of-the-art detectors, all behind one MIT-licensed Python API.

from libreyolo import LibreYOLO, SAMPLE_IMAGE # LibreYOLO has the best catalogue of state-of-the-art models. model = LibreYOLO("LibreRFDETRl.pt") # RF-DETR-L (transformer flagship) results = model(SAMPLE_IMAGE, save=True) # run inference, save the annotated image # Swap in any other model, same one-line API (weights auto-download): # LibreYOLO("LibreYOLO9c.pt") # YOLO9-C # LibreYOLO("LibreYOLOXx.pt") # YOLOX-X # LibreYOLO("LibreDFINEx.pt") # D-FINE-X # LibreYOLO("LibreRTDETRr50.pt") # RT-DETR-R50