# dusty-nv/jetson-containers

Machine Learning Containers for NVIDIA Jetson and JetPack-L4T

Repository: https://github.com/dusty-nv/jetson-containers
Canonical: https://ross.abutalabs.com/products/jetson-containers
Language: Jupyter Notebook
License: NOASSERTION
License Family: other
Topics: machine-learning, dockerfiles, jetson, pytorch, tensorflow, pandas, scikit-learn, numpy, ros-containers, ros2-foxy, docker, containers, nvidia
Last push: 2026-08-10T06:35:47+00:00

## Health v2 (maintenance only)
Score: 76/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 97, release rhythm 35, longevity 100
- inputs: {"age_days": 2317, "days_push": 23, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 4835, forks 843 (observed 2026-08-28T04:09:00.652702+00:00)

## What it is
A modular Docker container build system providing prebuilt AI/ML packages (PyTorch, TensorFlow, vLLM, ollama, ROS, etc.) for NVIDIA Jetson devices running JetPack/L4T. It automates building and chaining container images optimized for Jetson's ARM64 CUDA environment.

## Use cases
- run pytorch or tensorflow on nvidia jetson
- deploy llm inference like vllm or ollama on jetson
- build docker containers for jetpack l4t
- run ros2 robotics containers on jetson
- set up machine learning environment on jetson orin nano
- get prebuilt cuda wheels for jetson arm64

## When to choose
- you develop AI/ML or robotics applications on NVIDIA Jetson hardware
- you need prebuilt CUDA/ML packages that are hard to compile on ARM64
- you want a reproducible containerized ML stack for edge deployment

## When to avoid
- you target x86 servers or cloud GPUs rather than Jetson devices
- you need a general-purpose Docker image registry unrelated to NVIDIA Jetson
- you don't use containers or Docker in your workflow

## Facets
- artifact type: infra-config
- maturity: active
- function: machine-learning, llm-inference, deep-learning, container-runtime, deployment, developer-tools
- domain: machine-learning, deep-learning, large-language-models, robotics, gpu-computing, developer-tools
- platform: -
- tags: nvidia-jetson, jetpack, dockerfiles, edge-ai, arm64, cuda, robotics, containers, docker, linux, arm, gpu

## Member repositories
- dusty-nv/jetson-containers (main) score 76

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:00.652702+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:18:29.393363+00:00, confidence not recorded.
  - readme: https://github.com/dusty-nv/jetson-containers (fetched 2026-08-28T04:09:00.652702+00:00, sha cc68723052ca)
- Data as of 2026-08-30T08:39:29.467469+00:00.