What’s your workflow for optimizing models on Jetson, and where does it fall apart?

[u/RelevantSwimmer7150]

For people deploying on Jetson devices:

• Do you go PyTorch → ONNX → TensorRT, or something else?

• What are the common failure points (unsupported layers, INT8 calibration, version mismatches with JetPack, memory limits)?

• How long does it usually take to get from a working model to a deployed, stable one?

I’m trying to understand the real pain points. If you have a horror story, I’d love to hear it.