Performance difference with compute capability jetson orin nano vs gtx 2070

Autonomous Machines Jetson & Embedded Systems Jetson Orin Nano
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I have configured my Jetson Orin Nano with JetPack 5.1, CUDA 11.4, and I am running a script for object detection with YOLOv8. When compared to a similar setup on my notebook with a GTX 2070 graphics card, the performance difference is abysmal, in favor of the notebook, as seen in the video. Is such a difference to be expected? Both are running the same model converted from PyTorch to TensorRT with the configuration half=True, simplify=True, and both support CUDA. My question refers to the fact that, on NVIDIA’s official site, the GTX 2070 has a ‘compute capability’ of 7.5, while the Jetson Orin Nano has a compute capability of 8.7.
Thanks

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related: Jetson Orin nano v/s gtx 2070 - #2 by Robert_Crovella

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Hi,

Is the left-hand the result of Orin Nano?
If yes, do you want to ask why Orin Nano runs slower even though the architecture is newer?

If yes, have you maximized the device performance first?
Then, would you mind monitoring the device to see if the GPU utilization is saturated not not?

$ sudo tegrastats

Thanks.

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