# Python 3.12 and PyTorch Support on BalenaOS for Jetson Orin

**URL:** <https://forums.balena.io/t/python-3-12-and-pytorch-support-on-balenaos-for-jetson-orin/375084>\
**Category:** balenaOS\
**Tags:** jetson\
**Created:** [November 14, 2025, 11:59am UTC](https://forums.balena.io/t/python-3-12-and-pytorch-support-on-balenaos-for-jetson-orin/375084 "2025-11-14T11:59:23Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![GonzaloLoureiro](https://avatars.discourse-cdn.com/v4/letter/g/ce7236/32.png) [@GonzaloLoureiro](https://forums.balena.io/u/GonzaloLoureiro)\
**Post date:** [November 14, 2025, 11:59am UTC](https://forums.balena.io/t/python-3-12-and-pytorch-support-on-balenaos-for-jetson-orin/375084/1 "2025-11-14T11:59:23Z")

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Hi All, We are currently deploying a PyTorch-based AI application to Jetson Orin devices managed by BalenaOS. We’ve run into a significant container incompatibility issue and wanted to ask for your guidance on the recommended path forward.Our goal was to use Python 3.12, but we encountered a series of cascading incompatibilities:

1. NVIDIA Image Failure: Using a standard NVIDIA image (like [`nvcr.io/nvidia/pytorch:25.06-py3-igpu`](http://nvcr.io/nvidia/pytorch:25.06-py3-igpu)) failed, as it’s not compatible with BalenaOS’s specific driver provisioning model for the Jetson GPU.

2. Custom Build Failure: We then tried building on a Balena-compatible base image ([https://github.com/balena-io-examples/jetson-examples/blob/master/jetson-orin/Dockerfile](https://github.com/balena-io-examples/jetson-examples/blob/master/jetson-orin/Dockerfile)) and manually installing Python 3.12 on top of it. This failed because there are no official, Jetson-specific PyTorch wheels available for Python 3.12. The build was forced to use a generic `aarch64` wheel, which couldn’t access the Jetson GPU and crashed.

Our short-term resolution has been to revert our application’s dependencies to Python 3.10 to remain compatible with the base image and the available Jetson-specific PyTorch wheels.

This leads to our questions for your team:

1. Is reverting to Python 3.10 (and its compatible PyTorch wheel) the current, officially recommended path for deploying GPU-accelerated PyTorch apps on BalenaOS for Jetson Orin? We ask as Python 3.10 reaches its end-of-life in October 2026, so we are keen to understand the future-proof path.

2. Are there any plans for a Balena-compatible base image for Jetson Orin that will officially support Python 3.12 and the necessary hardware-accelerated libraries?

3. If we have a hard requirement for Python 3.12, would you recommend we build PyTorch from source inside our container? If so, are there any Balena-specific guides or best practices for this, especially concerning the driver interactions and build environment?

Thank you for your time and any guidance you can provide.