Supported Models

This page lists all models currently supported by trtutils.

Object Detection

YOLO Models

  1. Ultralytics YOLO - YOLOv8 and YOLOv11

    • YOLOv8: yolov8n, yolov8s, yolov8m, yolov8l, yolov8x

    • YOLOv11: yolov11n, yolov11s, yolov11m, yolov11l, yolov11x

    • GitHub: ultralytics/ultralytics

  2. YOLOv7

  3. YOLOv9

  4. YOLOv10

  5. YOLOv12

  6. YOLOv13

  7. YOLOX

DETR Models

  1. RT-DETRv1

  2. RT-DETRv2

  3. RT-DETRv3

  4. D-FINE

  5. DEIM

  6. DEIMv2

  7. RF-DETR

Classification

  1. Torchvision Classifiers

Model Download Support

The following models can be automatically downloaded and converted to ONNX format using the download CLI command:

YOLO Models

  • YOLOv7: All variants with pretrained weights

  • YOLOv8: yolov8n, yolov8s, yolov8m, yolov8l, yolov8x (via Ultralytics)

  • YOLOv9: All variants with pretrained weights

  • YOLOv10: All variants with pretrained weights

  • YOLOv11: yolov11n, yolov11s, yolov11m, yolov11l, yolov11x (via Ultralytics)

  • YOLOv12: All variants with pretrained weights

  • YOLOv13: yolov13n, yolov13s, yolov13l, yolov13x

  • YOLOX: yoloxn, yoloxt, yoloxs, yoloxm, yoloxl, yoloxx, yolox_darknet

DETR Models

  • RT-DETRv1: Multiple configurations available

  • RT-DETRv2: Multiple configurations available

  • RT-DETRv3: Multiple configurations available

  • D-FINE: Multiple configurations available

  • DEIM: Multiple configurations available

  • DEIMv2: deimv2_atto, deimv2_femto, deimv2_pico, deimv2_n, deimv2_s, deimv2_m, deimv2_l, deimv2_x

  • RF-DETR: Multiple configurations available

Example Usage

Download models using the CLI:

$ python -m trtutils download --model yolov8n --output yolov8n.onnx
$ python -m trtutils download --model yolov11m --output yolov11m.onnx --imgsz 640 --opset 17
$ python -m trtutils download --model yoloxs --output yoloxs.onnx --imgsz 640 --opset 17

For more information on the download command, see the CLI Reference.