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Running Gen AI models and applications on NVIDIA Jetson devices with one-line command

Project description




This repository provides examples for running AI models and applications on NVIDIA Jetson devices with a single command.

This repo builds upon the work of the jetson-containers, which provides a modular container build system for various AI/ML packages on NVIDIA Jetson devices.


  • 🚀 Easy Deployment: Deploy state-of-the-art AI models on Jetson devices in one line.
  • 🔄 Versatile Examples: Supports text generation, image generation, vision transformers, computer vision and so on.
  • Optimized for Jetson: Leverages Nvidia Jetson hardware for efficient performance.


To install the package, run:

pip3 install jetson-examples


  • Check here for more installation methods
  • To upgrade to the latest version, use: pip3 install jetson-examples --upgrade.


To run and chat with LLaVA, execute:

reComputer run llava

Example list

Here are some examples that can be run:

Example Type Model/Data Size Docker Image Size Command
🆕 yolov10 Computer Vision 7.2M 5.74 GB reComputer run yolov10
🆕 llama3 Text (LLM) 4.9GB 10.5GB reComputer run llama3
🆕 ollama Inference Server * 10.5GB reComputer run ollama
LLaVA Text + Vision (VLM) 13GB 14.4GB reComputer run llava
Live LLaVA Text + Vision (VLM) 13GB 20.3GB reComputer run live-llava
stable-diffusion-webui Image Generation 3.97G 7.3GB reComputer run stable-diffusion-webui
nanoowl Vision Transformers(ViT) 613MB 15.1GB reComputer run nanoowl
nanodb Vector Database 76GB 7.0GB reComputer run nanodb
whisper Audio 1.5GB 6.0GB reComputer run whisper
yolov8-rail-inspection Computer Vision 6M 13.8GB reComputer run yolov8-rail-inspection
ultralytics-yolo Computer Vision 15.4GB reComputer run ultralytics-yolo
depth-anything Computer Vision 12.9GB reComputer run depth-anything

Note: You should have enough space to run example, like LLaVA, at least 27.4GB totally

More Examples can be found


Want to add your own example? Check out the development guide.

We welcome contributions to improve jetson-examples! If you have an example you'd like to share, please submit a pull request. Thank you to all of our contributors! 🙏


  • check disk space enough or not before run
  • allow to setting some configs, such as BASE_PATH
  • detect host environment and install what we need
  • support jetson-containers update
  • all type jetson support checking list
  • better table to show example's difference
  • try jetpack 6.0


This project is licensed under the MIT License.


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