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NVIDIA

NVIDIA Jetson Orin Nano Super Developer Kit

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Features

  • The NVIDIA Jetson Orin Nano Developer Kit sets a new standard for creating entry-level AI-powered robots, smart drones, and intelligent cameras,and simplifies getting started with the Jetson Orin Nano series. Compact design, lots of connectors and up to 40 TOPS of AI performance make this developer kit perfect for transforming your visionary concepts into reality. With up to 80X the performance of Jetson Nano, it can run all modern AI models, including transformer and advanced robotics models.
  • The developer kit comprises a Jetson Orin Nano 8GB module and a reference carrier board that can accommodate all Orin Nano and Orin NX modules, providing an ideal platform for prototyping your next-gen edge AI product. The Jetson Orin Nano 8GB module features an Ampere GPU and a 6-core ARM CPU, enabling multiple concurrent AI application pipelines and high-performance inference. The carrier board boasts a wide array of connectors, including two MIPI CSI connectors supporting camera modules with up to 4-lanes, allowing higher resolution and frame rate than before.
  • Jetson runs the NVIDIA AI software stack, with available use-case-specific application frameworks, including NVIDIA Isaac for robotics, DeepStream for vision AI, and Riva for conversational AI. You can save significant time with NVIDIA Omniverse Replicator for synthetic data generation (SDG), and with NVIDIA TAO Toolkit for fine-tuning pretrained AI models from the NGC catalog.
  • Ecosystem partners offer additional AI and system software, developer tools, and custom software development. They can also help with cameras and other sensors, as well as carrier boards and design services for your product.
  • Jetson Orin modules are unmatched in performance and efficiency for robots and other autonomous machines, and give you the flexibility to create the next generation of AI solutions with the latest NVIDIA technology. Together with the world-standard NVIDIA AI software stack and an ecosystem of services and products, your road to market has never been faster.

Description

The NVIDIA Jetson Orin™ Nano Super Developer Kit is a compact, yet powerful computer that redefines generative AI for small edge devices. It delivers up to 67 TOPS of AI performance—a 1.7X improvement over its predecessor—to seamlessly run all kinds of generative AI models, like vision transformers, large language models, vision-language models, and more. At just $249, it provides developers, students, and makers with the most affordable and accessible platform with the support of the NVIDIA AI software and a broad AI software ecosystem to democratize generative AI at the edge. Existing Jetson Orin Nano Developer Kit users can experience this performance boost with just a software upgrade, so everyone can now unlock new possibilities with generative AI. The developer kit comprises a Jetson Orin Nano 8GB module and a reference carrier board that can accommodate all Orin Nano and Orin NX modules, providing an ideal platform for prototyping your next-gen edge AI product. The Jetson Orin Nano 8GB module features an Ampere GPU and a 6-core ARM CPU, enabling multiple concurrent AI application pipelines and high- performance inference. The carrier board boasts a wide array of connectors, including two MIPI CSI connectors supporting camera modules with up to 4-lanes, allowing higher resolution and frame rate than before. Jetson runs the NVIDIA AI software stack, with available use-case-specific application frameworks, including NVIDIA Isaac™ for robotics, NVIDIA Metropolis™ for vision AI, and NVIDIA Holoscan™ for sensor processing. You can save significant time with NVIDIA Omniverse™ Replicator for synthetic data generation (SDG), and with NVIDIA TAO Toolkit for fine-tuning pretrained AI models from the NGC™ catalog. Ecosystem partners offer additional AI and system software, developer tools, and custom software development. They can also help with cameras and other sensors, as well as carrier boards and design services for your product. Jetson Orin modules are unmatched in performance and efficiency for robots and other autonomous machines, and give you the flexibility to create the next generation of AI solutions with the latest NVIDIA technology. Together with the world-standard NVIDIA AI software stack and an ecosystem of services and products, your road to market has never been faster.

Brand: NVIDIA


Model Name: Jetson Orin Nano 8GB


Ram Memory Installed Size: 8 GB


Memory Storage Capacity: 8 GB


CPU Model: 6-core ARM Cortex-A78AE v8.2


RAM Memory Installed: 8 GB


Memory Storage Capacity: 8 GB


CPU Model: 6-core ARM Cortex-A78AE v8.2


Connectivity Technology: USB, DisplayPort, Ethernet, GPIO


Operating System: Linux


Processor Brand: ARM


Wireless Compability: Bluetooth


Compatible Devices: Various


RAM Memory Technology: LPDDR4X


Processor Count: 1


Total Usb Ports: 5


Item Dimensions L x W x H: 6"L x 3"W x 8"H


Brand: NVIDIA


Model Name: Jetson Orin Nano 8GB


Built-In Media: Quick Start and Support Guide, Type B (US, JP) Power Cable, Type I (CN) Power Cable


Number of Packs: 1


Number of Items: 1


UPC: 812674025261


Unit Count: 1 Count


Global Trade Identification Number: 61


External Testing Certification: Não Aplicável


Item Weight: 1.8 pounds


Manufacturer: NVIDIA


Model Number: 945-137766-0000-000


Mfr Part Number: 945-137766-0000-000


Warranty Description: 1 year manufacturer


Frequently asked questions

If you place your order now, the estimated arrival date for this product is: Oct 10 – Oct 11

Yes, absolutely! You may return this product for a full refund within 30 days of receiving it.

To initiate a return, please visit our Returns Center.

View our full returns policy here.

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Top Amazon Reviews

    • Read Up! Add the M2 drive, once you get it running the base make a solid backup and then go off!!
Style: Developer Kit
I love this thing! I had so much fun setting it up, had it orchestrate my two AI servers to build my from scratch Chess AI model. Now it’s my personal assistant that I built an MCP server to do Web Searches for me, analyzes the data and returns the top finds. Hosts a web chat and handles the AI party members for the old school D&D game I wrote, over 300 tools on an MCP server for the D&D game(5b Q4 model open source) Runs Chess, connect 4, 5 in a row, tic tac toe and soon backgammon(my 18M model). It has limits due to 8GB VRAM but this is a solid device, and will soon control my robot pi tank over wifi, I paid $250 for it, $50 128GB m2, $20 case and I had a micro SD. So $320 for a solid device. I skipped the docker and openclaw and built my own agent. I set up Tailscale on it so I can get to it from anywhere Ollama Llama Llama! :) So many models run very well on this thing! If it drops to $250 again I’ll buy another! Maybe 2 to run home automation and replace that A letter device ;) why do I have to connect to the internet to turn off my lamp? And handle my side gig invoices and bill pay, another MCP server coming soon. It’s running 2 MCP servers, 1 web chat server and the 7b model extremely well! Nvidia! It is the way! Super Happy I got this. This price isn’t terrible but I’m waiting for it to drop since I have one and 2 AI servers… dang I’m a nerd! ... show more
Reviewed in the United States on August 5, 2026 by R Barry Ellison jr
    • works for training models using transformers just fine (just the normal nvidia python issues suck)
Style: Developer Kit
so far, its been pretty good, BUT NVIDIA drivers and Linux..... DUDE... its a PITA. When you do get the system up and running with linux drivers with all of the CUDA and the python support is finally working right (NVIDIA keeps changing python libraries without keeping a steady version numbering on their wheels or just deleting them without letting people know) its good. Currently using mine to build Ai models using transformers on market history for daytrading crypto. Works pretty good, i have my script on github... thing is i keep finding little changes i can add to the scrypt so i've only posted the main scrypt on github, and haven't settled on a new updated version yet till i work the bugs out of the jetson and the scrypt. ... show more
Reviewed in the United States on May 7, 2026 by Jason C. Wise
    • Irritating to set up but runs like a dream once it is.
Style: Developer Kit
This thing is a colossal pain in the ass to set up. My advice, skip the messing around with SD cards etc. Take a old laptop, install Nvidia Ubuntu with console, and install it directly to the nvme (get one too, you'll thank me). No cards no bs. You will probably need to build llama.cpp from source to integrate the cuda cores etc so it can take care of the hardware for inference. But once that's all done and set up, it runs great. I keep it at max power, running qwen 3.5 3B with vision. And I get around 16+ tokens a second. Pain to set up but worth it. ... show more
Reviewed in the United States on March 16, 2026 by Ryan Robinson
    • Excellent – Powerful, Fast, and Perfect for Advanced AI Projects
Style: Developer Kit
The NVIDIA Jetson Orin Nano Super Developer Kit exceeded every expectation. For its size, this thing delivers incredible performance — fast boot times, smooth CUDA acceleration, and outstanding handling of AI workloads. Running local LLMs, vision models, robotics stacks, and edge-compute pipelines feels effortless. The build quality is solid, setup is straightforward, and the system stays stable even under heavy loads. I’ve tested everything from PyTorch models to engineering diagnostics and it never struggles. For anyone working on edge AI, embedded systems, or real-time machine learning, this is an absolute powerhouse. Highly recommended if you want serious AI performance in a compact, efficient developer kit. This is hands-down one of the best edge-AI boards available right now. ... show more
Reviewed in the United States on November 15, 2025 by Picasso
    • Build your own AI toaster, after historical depency resolution
Style: Developer Kit
Computers aren't toasters. NVIDIA thinks they are selling build-your-own toasters with these Jetson devices. Except there are no slots for the bread, and if you try to put them in, you might have to recompile the Linux Kernel. Against better judgment. So I'm not sure what the appliance is or will be. Good luck to the brave who have to enforce a standard for a particular build of this thing. I'm sure that the "stability" of a control build of you're device/application will be crushed by the never-ending parade of CVEs that plague networked devices. At the moment, applications on this nano will likely break on the newest version of Docker that patches a pre-auth RCE. Wait.. don't want to use Docker? Good luck if you try to do something bare metal; you're relegating yourself to the point in history this device came from. Also, if you plan to effectively air-gap, good luck matching your dependencies with system interfaces from 5 years ago. Their tune might be changing on this with more recent Jesons, but I'm sure there will still be lags by arrogantly trying to freeze a moment in time. Just because we have version control doesn't mean you can stop time or truly turn it back; in fact, with Git, you can rewrite history if you're so adventurous. I'm not sure anybody appreciates a denial of reality. Please, NVIDIA, just switch to fix forward. The people who need control builds will figure it out. I'm 0 for 2 for networking cards on getting wireless working with the kernel/bootload combo that does super mode (the one that came with it probably works, on the kernal that ships with the device, I didn't test that). Also, hosed my application by neively sudo apt update && sudo apt upgrade. This is where the docker issue above presents itself, you'll have to pin everything to stay stable. Also note that this doesn't ship with "super mode" firmware-wise, which is an Odyssey adventure to enable. Just get the NVIDIA driver manager (sign the TOS), install the newest old one (5.w.e), then install the newest new one (6.w.e) for this device... no prob, your favorite AI tool will help you. People in this review column are saying to be cautious: this is a "dev device," which I guess means something somewhat accurate, but to be more specific, this is the type of thing you buy and feels like false-capability advertising because the juice isn't worth the squeeze unless you absolutely need CUDA at this price point. I think that's what people mean when they say it didn't "perform" as expected. If it does perform as expected, it'll probably take me more than a hot minute to figure that out if I didn't have something better to do. On a positive note, the form factor is much more compact than expected. Very cute. ... show more
Reviewed in the United States on January 31, 2026 by Paul Beaudet
    • Nice
Style: Developer Kit
Bought this to keep my gpu skills up and to add to my home lab. Nice little setup for what I needed.
Reviewed in the United States on August 9, 2026 by David L. Whiteside
    • It's a great board but the setup is not for the faint of heart
Style: Developer Kit
Review Image by Horace P.
I’ve been extremely impressed with the NVIDIA Jetson Nano Super Developer Kit 8GB. For anyone seriously interested in exploring local AI, edge inference, robotics, or embedded AI systems, this little board is an absolute hammer for the price and power envelope. Performance-wise, I was able to achieve over 20 tokens/sec running an 8B model locally, which honestly exceeded my expectations for hardware in this class. NVIDIA’s CUDA ecosystem, TensorRT support, and overall AI tooling make this platform feel much more capable than its size would suggest. It punches well above its weight. That said, I do want to give one honest caveat: setup can be challenging. I’ve configured two of these boards now, and both took nearly a full day of troubleshooting, flashing, configuring, and tuning before everything was stable and running correctly. This is definitely more of an engineer/developer platform than a consumer plug-and-play device. However, if you’re comfortable working through Linux setup, drivers, SDKs, containers, or AI frameworks, the payoff is absolutely worth it. Once configured properly, this thing becomes an incredibly capable local AI platform. Highly recommended for developers, makers, robotics enthusiasts, and anyone wanting to learn real edge AI without spending workstation-level money. ... show more
Reviewed in the United States on May 19, 2026 by Horace P.
    • An absolute monster of a board!
Style: Developer Kit
Review Image by RPDevJesco
Review Image by RPDevJesco
First things first, this board is absolutely beautifully designed. The location of the SD Card and where you can add your NVMe drives make logical sense. It ships with factory firmware that requires an update before use. It is a bit of work to find the firmware update and is a rather large file that you will then need to flash onto an SD Card using BalenaEtcher, which is about 30 minutes of waiting depending on your download and cpu speeds. The UEFI bios is very well organized and structured and does have TPM 2.0. It does not have an OS installed by default, so you will need to install one via SD Card or NVMe slots. Which means you can use official Nvidia images or you can use custom ones. The official image is also a bit of a pain to find, but again, once you download it, you need to flash it onto an SD Card using BalenaEtcher. Your mileage may vary for how long this process will take. For me, it was around 10 minutes. The construction of this thing is super solid. Has a very solid base that the SBC connects to, the CPU is more of a Compute module setup so you could possibly change it for a newer MU unit later without needing a new base. The standard use case for a board like this is local LLM inference, my use case is currently getting my custom OS to boot on it and then move to local LLM inference later. ... show more
Reviewed in the United States on February 19, 2026 by RPDevJesco

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