Skip to content
Hi, Bot
Back to blog
jetsonaihardwaretutorialedge-aigetting-started

Getting Started with the Jetson Orin Nano Super: The Complete Beginner's Guide

Step-by-step tutorial to unbox, set up, and run your first AI project on the Jetson Orin Nano Super. Includes what not to do, troubleshooting, and three working projects.

June 10, 2026 · Hi, Bot

What You're About to Do

Congratulations! You just got your hands on one of the smallest, most powerful AI computers in the world. The Jetson Orin Nano Super can run advanced AI models—like real-time object detection, language models, and robotics software—all by itself, without needing the cloud.

This guide will walk you through everything: getting it set up, turning it on, and running your first AI project. We'll also show you exactly where people mess up (so you won't), and how to make the most of your new machine.

What makes the "Super" special?

  • 67 trillion operations per second (INT8 TOPS) for AI tasks
  • 2x faster memory access than the regular Orin Nano
  • Powerful enough to run generative AI models locally
  • Uses only 7–25 watts of power (fits on a desk)

Module 1: Get Your Physical Setup Right

The Hardware Checklist

Before you start downloading anything, gather these items:

Absolutely Required:

  • ☑ Your Jetson Orin Nano Super Developer Kit (the black carrier board + gray module with heatsink)
  • ☑ One of: Recommended option: 256GB M.2 NVMe SSD in a USB 3.0 enclosure, OR Good option: 128GB microSD card (UHS-I minimum; Kingston, Samsung, or SanDisk work best)
  • ☑ The included power supply (DC barrel connector, supports up to 25W)
  • ☑ A monitor with HDMI or DisplayPort
  • ☑ USB keyboard
  • ☑ USB mouse
  • ☑ An Ethernet cable OR a Wi-Fi adapter (the kit has Ethernet built in)
  • ☑ A second computer (Windows, Mac, or Linux) to flash your storage before plugging it into the Jetson

Nice to Have:

  • A USB hub with external power (to avoid voltage drops when plugging in multiple things)
  • A small desk fan pointing at the heatsink (for heavy AI workloads)
  • A 5V micro-USB cable for powering any add-on sensors

Storage Choice: Which Is Right for You?

microSD Card:

  • ✅ Cheaper
  • ✅ Easier to swap
  • ❌ Slower (can struggle with large AI models)
  • ❌ More likely to corrupt if the power cuts

NVMe SSD (Recommended):

  • ✅ 10–100x faster than SD cards
  • ✅ Can store 256GB+ of AI models
  • ✅ Won't choke under heavy loads
  • ✅ More professional
  • ❌ Costs a bit more upfront

Pro Tip: If you're serious about running multiple AI models or doing robotics, go with the NVMe SSD. You'll save yourself headaches later.

› Go deeper on Hi, Bot

Toolkit — what to actually buy. The build-or-buy parts list, the SSD-vs-microSD math, and the cooling/power add-ons that keep your kit happy are packaged in the Jetson Build Lab — our guided project pack for the Orin Nano Super. Want the short version now? Jump to storage troubleshooting and power modes.

→ See the Jetson Build Lab

Module 2: Prepare Your Operating System

Choose Your Path

Path A: Fresh Start (New Kit) You'll download the Jetson software and "flash" it onto your storage.

Path B: Upgrade (Existing Orin Nano) You'll update your software to unlock the Super's full power.

Path A: Setting Up a Brand-New Kit

Step 1: Download the Jetson OS

  1. On your host PC (the computer you're using right now, not the Jetson), open a web browser.
  2. Go to: NVIDIA Jetson Developer Downloads
  3. Look for "Jetson Linux 35.x or newer" (specifically, find the SD Card Image for Jetson Orin Nano)
  4. Check the filename: it should say something like Jetson_Linux_R36_aarch64.iso or orin-nano-sd-card-image.zip
  5. Click Download and wait. The file is ~5–8 GB, so this might take a while.

⚠️ How NOT to Mess Up:

  • Don't download the wrong image (there's one for Orin Nano, Orin NX, Orin AGX—get the Nano one)
  • Don't interrupt the download halfway through
  • Don't try to unzip it manually—the flashing tool will handle that

Step 2: Flash Your Storage Medium

Flashing means copying the operating system onto your storage device so the Jetson can boot from it.

If You're Using an NVMe SSD:

  1. On your host PC, download balenaEtcher (it's free)
  2. Install balenaEtcher and launch it
  3. Plug your NVMe SSD into a USB 3.0 enclosure, then plug that into your host PC
  4. In balenaEtcher:
    • Click Flash from file → select the .iso or .zip you downloaded
    • Click Select target → choose your USB-connected SSD (double-check the name/size!)
    • Click Flash!
  5. Wait 5–15 minutes. You'll see a progress bar.
  6. When it says "Flash complete!", eject the SSD safely from your host PC
  7. Put the SSD into the M.2 slot on the underside of your Jetson (see Step 1 under "Hardware Assembly")

If You're Using a microSD Card:

  1. Plug your microSD card into your host PC (using a USB adapter if needed)
  2. Follow the same balenaEtcher steps above
  3. When flashing is complete, eject the card and set it aside (you'll insert it into the Jetson later)

⚠️ How NOT to Mess Up:

  • Triple-check that you're selecting the right drive in balenaEtcher. Flashing erases everything on that drive
  • Don't unplug the SSD/card while it's flashing
  • Don't use slow USB 2.0 cables—use USB 3.0 (usually blue ports) for faster flashing
  • If balenaEtcher says "Target is too small," your storage device isn't big enough. Get a larger one

✓ Thrive Tip: Keep your storage device plugged into your host PC until you're 100% sure the flash worked. You can verify by opening the file manager—you should see a boot folder and other Linux directories. If the drive looks empty or corrupted, try flashing again.

› Go deeper on Hi, Bot

Toolkit — flash it once, flash it right. A printable flash-verification checklist (the "is the boot folder really there?" test) and a JetPack version cheat-sheet ship with the Jetson Build Lab. If a flash goes sideways, the fixes live in Troubleshooting.

→ Start an Activities trial

Path B: Upgrading an Existing Jetson Orin Nano

If you're upgrading from a regular Orin Nano, you don't need to reflash—you just update the software.

Step 1: Backup Your Work

  1. Plug in a USB flash drive
  2. Open the file manager and navigate to your home folder (/home/your_username/)
  3. Copy any important Python scripts, Docker containers, or AI models to the USB drive
  4. Eject the USB drive safely

Step 2: Perform the Software Upgrade

  1. Open a terminal (right-click on the desktop → "Open Terminal Here" or press Ctrl + Alt + T)
  2. Run these three commands one at a time:
sudo apt update

Wait for it to finish, then:

sudo apt dist-upgrade

(This one takes longer—5–10 minutes. Let it run.)

Finally:

sudo apt install nvidia-jetpack
  1. The system will ask: Do you want to continue? [Y/n] — type Y and press Enter
  2. When it finishes, the terminal will prompt you to reboot. Type:
sudo reboot

Your Jetson will restart and apply the upgrades. You'll see the login screen again. Log back in with your password.

⚠️ How NOT to Mess Up:

  • Don't close the terminal or unplug the power during these updates
  • Don't panic if it seems to hang for a minute—large updates take time
  • If the terminal shows an error, screenshot it and paste it into the NVIDIA Jetson Forums (the community is friendly and helpful)

✓ Thrive Tip: After the upgrade, run jtop (see Module 4) to confirm that your clock speed jumped to 1.7 GHz and you're getting the full Super performance.

Module 3: Hardware Assembly and First Boot

Step 1: Assemble Your Kit

  1. Flip the Jetson over (heatsink facing down, toward the table)
  2. Insert your storage:
    • If using microSD card: Locate the slot on the underside and slide the card in until it clicks
    • If using NVMe SSD: Locate the M.2 slot, gently insert the SSD at a 45° angle, then push down and screw it tight with the tiny screw provided
  3. Connect your peripherals:
    • Plug your USB keyboard and mouse into the USB ports on the carrier board
    • Plug your monitor into the HDMI or DisplayPort
    • Plug an Ethernet cable into the Ethernet port (or skip this if you'll use Wi-Fi)
  4. Flip it right-side up and place it on a stable surface

Step 2: Power On

  1. Plug the barrel connector of the power supply into the Jetson
  2. Plug the power supply into a wall outlet
  3. You should see a green LED light up on the carrier board
  4. The screen will show the Ubuntu logo and boot messages (this takes 30–60 seconds on first boot)

⚠️ How NOT to Mess Up:

  • Don't force the microSD card or SSD into their slots—they should slide in smoothly
  • Don't plug the power in before you've connected your storage. The Jetson needs something to boot from
  • If you see a black screen for more than 2 minutes, your monitor cable might not be fully seated. Unplug it, wait 5 seconds, and plug it back in

Step 3: Ubuntu Setup Wizard

Once the desktop appears, you'll be greeted by the Ubuntu Initial Setup Wizard. Here's what to do:

  1. Accept the NVIDIA EULA — click "I Agree"
  2. Select your language — choose English (or your language)
  3. Set your timezone — pick your city/region from the list
  4. Create your user account:
    • Username: Pick something simple (e.g., jetson or your first name)
    • Password: Make it memorable—you'll type this dozens of times
    • Computer name: Something fun like jetson-ai or robot-brain
  5. If using NVMe SSD: You may see a screen asking about partition sizes. Choose the largest possible APP partition (usually already selected)
  6. Click Next and let the system complete setup
  7. The system will reboot, and you'll see the login screen

Log in with your username and password. You're now on your Jetson!

⚠️ How NOT to Mess Up:

  • Write down your password somewhere safe (you'll need it for sudo commands)
  • Don't choose a password you'll forget—this isn't something IT can reset
  • If setup hangs on "Expanding filesystems," give it 5 minutes before assuming it's frozen

✓ Thrive Tip: After logging in, open a terminal and run:

sudo apt update && sudo apt upgrade

This takes 5 minutes but ensures all your system patches are current.

› Go deeper on Hi, Bot

Add-ons — past the keyboard and mouse. Wiring your first sensor or LED to the 40-pin header is the gateway to real projects. The GPIO pinout poster and a first-sensor wiring card are part of the Jetson Build Lab. Confirm you've got full power first in Module 4.

→ See the Jetson Build Lab

Module 4: Verify You Have Full Power

Step 1: Install Jetson-Stats (The Best Monitoring Tool)

jtop is a terminal-based dashboard that shows you exactly what your Jetson is doing—CPU speed, memory, temperature, and power usage. It's essential.

Open a terminal and run:

sudo apt install python3-pip
sudo -H pip install -U jetson-stats

When it's done, reboot:

sudo reboot

After rebooting, open a terminal and type:

jtop

A fancy dashboard will appear. Press the Right Arrow key to navigate to the INFO tab.

What to Look For:

  • CPU Max Freq: Should show 1.7 GHz (if it shows 1.2 GHz, your power mode is too low)
  • RAM: Should show 8 GB
  • GPU Memory Bandwidth: Should show 102 GB/s (this is the "Super" upgrade)

If those numbers look right, congratulations—you've got full power!

Press q to exit jtop.

Step 2: Switch to Maximum Power Mode

By default, your Jetson might be in a power-saving mode. To unlock the full 25W of performance:

Option 1: GUI (Easiest)

  1. Look at the top-right corner of your desktop
  2. Click the NVIDIA logo (it might be a small icon)
  3. Select "Power Mode" and choose MAXN
  4. The system will reboot

Option 2: Terminal (If the GUI option isn't there)

sudo nvpmodel -m 0

Now when you run jtop, your power consumption should show 15–25W during heavy use.

⚠️ How NOT to Mess Up:

  • MAXN mode will run hotter and use more power—keep the fan pointed at your heatsink
  • Don't use MAXN mode if your Jetson is in a hot room—it'll thermal throttle
  • If you see Throttle: True in jtop, your system is getting too hot. Lower the power mode or improve ventilation

✓ Thrive Tip: Watch jtop while running your first AI model (see Module 5). You'll see the CPU, GPU, and memory light up. This is when your Jetson is actually working for you.

› Go deeper on Hi, Bot

Toolkit — read the dashboard like a pro. A jtop walkthrough worksheet and a power-mode decision card (when MAXN earns its heat vs. when to dial back) come with the Jetson Build Lab. Then put that power to work in Module 5.

→ Start an Activities trial

Module 5: Run Your First AI Project

Now the fun part—actually using your Jetson.

Project 1: Run a Local Language Model (Beginner-Friendly)

This project will run a small AI language model (like ChatGPT's smaller cousin) entirely on your Jetson, no internet required.

  1. Open a terminal
  2. Install Docker (the tool that runs containerized AI software):
sudo apt install docker.io
sudo usermod -aG docker $USER
newgrp docker
  1. Clone the Jetson Containers project:
git clone https://github.com/dusty-nv/jetson-containers.git
cd jetson-containers
  1. Run a small language model:
./run.sh $(./autotag ollama)

The first time you run this, it will download a container (~1–2 GB). Subsequent runs are instant.

  1. Once you see the prompt, type:
/pull phi

This downloads a small, fast language model (Phi-2, ~1.5 GB).

  1. Now ask it a question:
What is machine learning?

The model will respond—entirely on your Jetson, in real-time.

⚠️ How NOT to Mess Up:

  • The first download takes 10 minutes—don't close the terminal
  • If you see "Out of memory," try a smaller model like tinyllama instead of phi
  • If Docker commands fail, try logging out and logging back in to apply group permissions

✓ Thrive Tip: Once you get comfortable with this, try ollama models to see a list of available models. Smaller models (2–7B parameters) run fastest on the Orin Nano Super.

Project 2: Computer Vision (Detect Objects in Real-Time)

This project will show you real-time object detection on video streams.

  1. Open a terminal
  2. Run the DeepStream object detection demo:
deepstream-app -c /opt/nvidia/deepstream/deepstream/samples/configs/deepstream-app/source4_1080p_dec_infer-resnet_tracker_sgie_tiled_display_int8.txt

A window will pop up showing four video streams with AI-detected objects outlined and labeled (cars, people, bikes, etc.).

What you're seeing:

  • Real-time inference (AI predictions) on video
  • 10–20 FPS on a video feed
  • All running locally on your Jetson

Close the window to stop the demo.

⚠️ How NOT to Mess Up:

  • If no window appears, check that your monitor is plugged in and your display is detected
  • If the demo crashes, try a simpler config file:
deepstream-app -c /opt/nvidia/deepstream/deepstream/samples/configs/deepstream-app/source1_usb_dec_infer_resnet_tracker_sgie_tiled_display_int8.txt

Project 3: Build Your Own AI Project

Once you're comfortable, you can build your own. Popular starting points:

  • Robotics: Follow NVIDIA Isaac tutorials (great for drones, rovers)
  • Custom object detection: Train a model in Google Colab, then run it on your Jetson
  • AI chatbot: Combine Ollama (from Project 1) with a web interface
  • Video analytics: Connect a USB camera and run real-time detection

› Go deeper on Hi, Bot

Projects — the build ladder. "Build your own" is exactly where most kits stall out. The Jetson Build Lab turns it into a guided climb: local LLM → real-time vision → sensors & GPIO → a robot that sees — each level with its own supply list, extension challenges, and a finished-project rubric. Built for ages 13–16 (supervised). This is the part of the Activities Pass worth subscribing for on its own.

→ Open the Jetson Build Lab

Module 6: Troubleshooting

Black Screen on Boot

Problem: You see nothing on the monitor after plugging in power.

Solutions:

  1. Try unplugging and replugging the HDMI/DisplayPort cable (sometimes it doesn't seat right)
  2. Try a different monitor or cable
  3. Check that your storage (microSD/SSD) is inserted correctly
  4. If you're using an external SSD, try replugging the USB cable
  5. Try holding down the power button for 10 seconds to hard-reset, then power on again

If still nothing: Your storage might not have flashed correctly. Go back to Module 2 and re-flash it.

Running Out of Storage Space

Problem: Your system says "No space left on device" and you can't install anything.

Cause: AI models are huge (some are 5–20 GB each).

Solutions:

  1. Check what's taking up space: 
    du -sh ~/
  2. If you have many Docker images, clean up: 
    docker system prune -a
  3. Better solution: Move to a larger NVMe SSD (1TB+) using NVIDIA's disk cloning tools or dd

System Gets Too Hot and Slows Down

Problem: Temperature in jtop shows 80°C+ and the system becomes sluggish.

Cause: Thermal throttling—the CPU reduces its speed to avoid overheating.

Solutions:

  1. Improve airflow: Point a desk fan at the heatsink
  2. Move your Jetson to a cooler room
  3. Lower the power mode temporarily: 
    sudo nvpmodel -m 1  # Medium power
  4. In jtop, press 5 to adjust the fan profile to "cool" or "active"

Stuck or Crashed AI Model

Problem: Your AI model starts and then freezes or crashes.

Cause: Usually out of memory or the model is too big.

Solutions:

  1. Open jtop in a separate terminal to watch memory usage
  2. If memory hits 100%, your model is too large
  3. Try a smaller model variant (e.g., tinyllama instead of phi)
  4. Allocate a GPU memory limit in your code (if you're writing Python)

Lost Your Password

Problem: You forgot your account password and can't use sudo.

Solution (if you have access to another admin):

sudo passwd your_username

If you're completely locked out, you can boot into recovery mode, but it's complex. Better to reach out to the NVIDIA Jetson Forums.

› Go deeper on Hi, Bot

Toolkit — a fix for every symptom. A printable symptom→fix decision tree (black screen, out-of-memory, thermal throttle, lost password) and a "when to ask the community" card ship with the Jetson Build Lab. Ready to build something bigger? Start the project ladder in Module 5.

→ See the Jetson Build Lab

Common Success Patterns

"I Want to Build a Robot"

  1. Follow the tutorials on NVIDIA Isaac ROS
  2. Start with a simulator first (Isaac Sim) before deploying on real hardware
  3. Join the Jetson Robotics community—lots of people are building cool stuff

"I Want to Run AI Models Locally"

  1. Use Ollama for language models (Project 1 above)
  2. Use ONNX Runtime for custom vision models
  3. Consider quantizing your models (int8) to run faster with less memory

"I Want to Deploy a Production System"

  1. Use Docker containers to package your app
  2. Set up monitoring with jtop or Prometheus
  3. Plan for thermal management and power budgeting
  4. Consider using NVIDIA's JetPack containers as a base

Next Steps: Join the Community

You're not alone in this journey. The Jetson community is huge and supportive.

Jump into:

Quick Reference: Key Terminal Commands

# Check your system specs
jtop

# Update your system
sudo apt update && sudo apt upgrade

# Install packages
sudo apt install <package_name>

# Check storage space
df -h

# Check temperatures
sudo tegrastats

# Set power mode (0 = MAXN, 1 = medium, 2 = low)
sudo nvpmodel -m 0

# Reboot
sudo reboot

# Shutdown safely
sudo shutdown -h now

You've Got This!

Setting up your Jetson Orin Nano Super is a big accomplishment. You now have a machine that can run state-of-the-art AI models locally, without needing the cloud, without monthly subscriptions, and with incredible power efficiency.

The hardest part is done. From here, it's all about experimenting, building, and pushing the boundaries of what's possible on the edge.

Welcome to the Jetson community. 🚀

› Keep reading

Get the next dispatch.

Occasional, never spammy.

By submitting, you agree to our Terms and Privacy Policy.