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Export mode is used for exporting a YOLOv8 model to a format that can be used for deployment. In this mode, the model is converted to a format that can be used by other software applications or hardware devices. This mode is useful when deploying the model to production environments.


  • Export to ONNX or OpenVINO for up to 3x CPU speedup.
  • Export to TensorRT for up to 5x GPU speedup.

Usage Examples

Export a YOLOv8n model to a different format like ONNX or TensorRT. See Arguments section below for a full list of export arguments.

from ultralytics import YOLO

# Load a model
model = YOLO('')  # load an official model
model = YOLO('path/to/')  # load a custom trained

# Export the model
yolo export format=onnx  # export official model
yolo export model=path/to/ format=onnx  # export custom trained model


Export settings for YOLO models refer to the various configurations and options used to save or export the model for use in other environments or platforms. These settings can affect the model's performance, size, and compatibility with different systems. Some common YOLO export settings include the format of the exported model file (e.g. ONNX, TensorFlow SavedModel), the device on which the model will be run (e.g. CPU, GPU), and the presence of additional features such as masks or multiple labels per box. Other factors that may affect the export process include the specific task the model is being used for and the requirements or constraints of the target environment or platform. It is important to carefully consider and configure these settings to ensure that the exported model is optimized for the intended use case and can be used effectively in the target environment.

Key Value Description
format 'torchscript' format to export to
imgsz 640 image size as scalar or (h, w) list, i.e. (640, 480)
keras False use Keras for TF SavedModel export
optimize False TorchScript: optimize for mobile
half False FP16 quantization
int8 False INT8 quantization
dynamic False ONNX/TF/TensorRT: dynamic axes
simplify False ONNX: simplify model
opset None ONNX: opset version (optional, defaults to latest)
workspace 4 TensorRT: workspace size (GB)
nms False CoreML: add NMS

Export Formats

Available YOLOv8 export formats are in the table below. You can export to any format using the format argument, i.e. format='onnx' or format='engine'.

Format format Argument Model Metadata
PyTorch -
TorchScript torchscript yolov8n.torchscript
ONNX onnx yolov8n.onnx
OpenVINO openvino yolov8n_openvino_model/
TensorRT engine yolov8n.engine
CoreML coreml yolov8n.mlmodel
TF SavedModel saved_model yolov8n_saved_model/
TF GraphDef pb yolov8n.pb
TF Lite tflite yolov8n.tflite
TF Edge TPU edgetpu yolov8n_edgetpu.tflite
TF.js tfjs yolov8n_web_model/
PaddlePaddle paddle yolov8n_paddle_model/