HELP: Running on JetPack 6.2

My use case is to run tensorrt compiled YOLOv8 models (ultralytics+onnx+onnxslim) on Server GPUs (Ubuntu Server 24.04) and Jetson GPUS (JetPack 6.2.1). While for servers we are simply using nvcr.io/nvidia/tritonserver:25.01-py3, it doesn't work on Jetson but no gpu is detected. I have tried older tags all the way down to 24.01-py3 with and without -igpu suffixes. Now the gpu works on Jetson with nvcr.io/nvidia/l4t-jetpack:r36.4.0 but the tritonserver tarball from release notes doesn't run on it. I have also tried older versions but no luck there seems be always a problem with compatibility.

Clearly we are doing something that jetson is prescribed for: Edge video processing with triton as part of a k8s cluster, where Jetsons are nodes with agent role and just the API for inference. We've had no luck with docker, containerd with or without k8s. We are using k3s, but I don't think this is relevant at all.

Can someone please tell me how are we supposed to do it with JP 6.2.1?

Which versions of the tarball are meant for which jetpack?

The issue names JetPack 6.2.1, nvcr.io/nvidia/l4t-jetpack:r36.4.0, Triton Server tarballs, Docker, containerd, and k3s, but no repository files or tests. Start by checking the release notes and compatibility information for the JetPack and Triton versions mentioned. Done would be a documented, verified version mapping and a supported deployment path for Jetson.