Export Table

{%set tip1 = ':material-information-outline:{ title="conf, iou, agnostic_nms are also available when nms=True" }' %} {%set tip2 = ':material-information-outline:{ title="IMX format is currently only supported for YOLOv8n, YOLO11n models" }' %}

Format	format Argument	Model	Metadata	Arguments
PyTorch	-	{{ model_name or "yolo26n" }}.pt	✅	-
[TorchScript]({{ integrations_path or "../integrations" }}/torchscript.md)	torchscript	{{ model_name or "yolo26n" }}.torchscript	✅	imgsz, quantize, dynamic, nms{{ tip1 }}, batch, device
[ONNX]({{ integrations_path or "../integrations" }}/onnx.md)	onnx	{{ model_name or "yolo26n" }}.onnx	✅	imgsz, quantize, dynamic, simplify, opset, nms{{ tip1 }}, batch, data, fraction, device
[OpenVINO]({{ integrations_path or "../integrations" }}/openvino.md)	openvino	{{ model_name or "yolo26n" }}_openvino_model/	✅	imgsz, quantize, dynamic, nms{{ tip1 }}, batch, data, fraction, device
[TensorRT]({{ integrations_path or "../integrations" }}/tensorrt.md)	engine	{{ model_name or "yolo26n" }}.engine	✅	imgsz, quantize, dynamic, simplify, opset, workspace, nms{{ tip1 }}, batch, data, fraction, device
[CoreML]({{ integrations_path or "../integrations" }}/coreml.md)	coreml	{{ model_name or "yolo26n" }}.mlpackage	✅	imgsz, dynamic, quantize, nms{{ tip1 }}, batch, device
[TF SavedModel]({{ integrations_path or "../integrations" }}/tf-savedmodel.md)	saved_model	{{ model_name or "yolo26n" }}_saved_model/	✅	imgsz, keras, quantize, opset, nms{{ tip1 }}, batch, data, fraction, device
[TF GraphDef]({{ integrations_path or "../integrations" }}/tf-graphdef.md)	pb	{{ model_name or "yolo26n" }}.pb	❌	imgsz, opset, batch, device
[TF Edge TPU]({{ integrations_path or "../integrations" }}/edge-tpu.md)	edgetpu	{{ model_name or "yolo26n" }}_edgetpu.tflite	✅	imgsz, quantize, opset, data, fraction, device
[PaddlePaddle]({{ integrations_path or "../integrations" }}/paddlepaddle.md)	paddle	{{ model_name or "yolo26n" }}_paddle_model/	✅	imgsz, batch, device
[MNN]({{ integrations_path or "../integrations" }}/mnn.md)	mnn	{{ model_name or "yolo26n" }}.mnn	✅	imgsz, batch, dynamic, quantize, simplify, opset, nms{{ tip1 }}, device
[NCNN]({{ integrations_path or "../integrations" }}/ncnn.md)	ncnn	{{ model_name or "yolo26n" }}_ncnn_model/	✅	imgsz, quantize, batch, device
[IMX500]({{ integrations_path or "../integrations" }}/sony-imx500.md){{ tip2 }}	imx	{{ model_name or "yolo26n" }}_imx_model/	✅	imgsz, quantize, data, fraction, nms{{ tip1 }}, device
[RKNN]({{ integrations_path or "../integrations" }}/rockchip-rknn.md)	rknn	{{ model_name or "yolo26n" }}_rknn_model/	✅	imgsz, batch, name, quantize, simplify, opset, data, fraction, device
[ExecuTorch]({{ integrations_path or "../integrations" }}/executorch.md)	executorch	{{ model_name or "yolo26n" }}_executorch_model/	✅	imgsz, batch, device
[Axelera]({{ integrations_path or "../integrations" }}/axelera.md)	axelera	{{ model_name or "yolo26n" }}_axelera_model/	✅	imgsz, batch, quantize, data, fraction, device
[DEEPX]({{ integrations_path or "../integrations" }}/deepx.md)	deepx	{{ model_name or "yolo26n" }}_deepx_model/	✅	imgsz, quantize, simplify, opset, data, optimize, device
[Qualcomm QNN]({{ integrations_path or "../integrations" }}/qnn.md)	qnn	{{ model_name or "yolo26n" }}_qnn.onnx	✅	imgsz, batch, name, quantize, simplify, opset, data, fraction, device
[LiteRT]({{ integrations_path or "../integrations" }}/litert.md)	litert	{{ model_name or "yolo26n" }}.tflite	✅	imgsz, quantize, batch, data, fraction, device
[Hailo]({{ integrations_path or "../integrations" }}/hailo.md)	hailo	{{ model_name or "yolo26n" }}_hailo_model/	✅	imgsz, name, quantize, data, fraction, simplify, conf, iou