Hey guys i'm trying to boot my jetson orin nano developer kit for the first time with an 256 gig sd card. I have successfully flashed the the os into the sd card with etcher, it completed and validated successfully, but when i power on my jetson with the sd card inserted, after the Nvidia screen I'm stuck here. Any help i could get would be greatly appreciated. Thank you. Is etcher the problem?
Hello everyone,
I bought jetson nano dev kit about 3 weeks ago with a lot of interest in starting with some projects. But, so far, I have had no success in setting it up. I am a beginner with these boards. Previously, I have only used Rpi 4 and 3 which seemed to be extremely easy to setup.
I have the following accessories:
I am following the intructions to install JetPack 6.2.1. I am at the section “Boot with JetPack 6.x SD Card” step 4. (link to instructions - here) Note: I do not have a Ubuntu OS on any of my other PCs.
After flashing the image to SD card, I power-on the jetson board and see the following screen:
Initially, after this screen, it would start logging a lot of lines on black screen starting with numbers or OK in square brackets.
While trying the same thing today, after this screen, the fan stops for a few seconds and then starts again. But, the screen is completely black now. I do not understand how to solve this issue.
I need help to solve this as soon as possible.
I tried to SSH via USB and Ethernet but no success. I think, during boot, it is not even able to reach the network setup stage.
My edge AI company is up and running. Venture's have been launched and we are driving toward our first revenue. Check out the build, the whole process is document! Jetson is the core!
We're running a monthly competition where you build an AI app that runs on real hardware (Jetson, phone, laptop), write it up, and the best entry wins $100 every month.
We provide pre-optimized models with Docker containers so you can skip a lot of the pains. Good way to get a real deployment experience and a write-up for your portfolio.
How to enter on Discord: https://discord.gg/MTbMWdKqE
I want to get into Edge AI deployment and want some suggestions for an application that I can make for my Jetson and have in my portfolio.
I’m looking at the NVIDIA Jetson Orin Nano Super Developer Kit and trying to work out whether this is a realistic use case for it today.
The rough idea would be:
I have a hosted GitLab server with internal documents, reports, notes, changelogs, or similar content.
Overnight, a CI pipeline would trigger a job that pulls the latest documents, processes them, publishes them internally, and then generates a useful summary of what changed or what people need to know.
Something like:
GitLab CI job runs on schedule
Pulls Markdown / PDFs / docs / repo content
Processes or converts them into an internal published format
Runs a local model or local inference step to summarise the content
Pushes the output somewhere internal
Maybe posts the summary back into GitLab, a dashboard, or chat
My question is: would the Jetson Orin Nano Super Developer Kit be suitable for this?
I know it is not a full workstation GPU, and I’m not expecting it to train models or run giant LLMs. I’m more thinking about lightweight local inference, document processing, embeddings, summarisation, maybe smaller quantised models, and general automation.
Would it be reasonably fast enough if the workload is overnight rather than interactive?
Would it make sense as a small local AI/automation box connected to GitLab CI, or would I be better off using a normal mini PC, cloud runner, Mac mini, or something with a stronger GPU?
I’m mainly interested in whether this is a practical setup in 2026, not whether it is technically possible in the most tortured way possible. I want to know if anyone is actually using Jetson devices for this kind of internal automation / document intelligence / CI-adjacent workflow and whether the experience is good or just painful.
I want to use the raspberry pi ai cam along with the jetson nano orin. Unfortunately I guess they are not compatible. Anyone ever tried this and it worked? there are only driver support for IM219 and 477 and not 500 which is the one used on the rpi AI cam. Any help is appreciated!
So far it has:
Next I want to pick some clothes like socks and put them into washing machine autonomously 😄
The Orange Pi 5 Plus in my stack serves as the Ollama model server, running qwen3.5:4b at about 7GB RAM. This week it powered something I'm pretty proud of.
My AI crew ran a complete local SEO campaign for a tattoo shop in San Diego. Here's what it generated automatically:
→ 8 keyword-optimized landing pages targeting San Diego
tattoo searches
→ 3 blog posts with proper meta descriptions and local
keyword targeting
→ 4 weeks of Google Business Profile posts
→ Review request SMS templates for the artists to send
after every appointment
→ Competitor research logged to PostgreSQL
The Orange Pi handled all the inference. Total AI cost for the content generation: about 30 cents in Claude API calls for the final polish pass.
A traditional SEO agency charges $1,500-2,500/month for this. The whole pipeline runs automatically every Monday morning via cron job.
Just posted a full video walkthrough showing exactly how it works, the agent architecture, the PostgreSQL schema, the Squarespace implementation, everything.
https://www.youtube.com/watch?v=a0NXVsqu5jQ
What are you all running on your Orange Pi?
Hi everyone, I’m a complete beginner planning to build an AI-powered "pet robot" that follows me around.
I’ve heard that since I have an RTX 4090, I should do all the heavy training on my PC first and then deploy (infer) the model onto the Jetson. Is this the standard workflow for a project like this? Any advice for a newbie would be much appreciated!
When choosing a model for Raspberry Pi / Jetson deployment, what’s the MOST frustrating part?
Trying to understand the biggest pain point before building a tool.
