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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: Saturday, Aug 29

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
    • Good for beginners
Style: Developer Kit
Review Image by Van
Review Image by Van
Jetson Orin Nano did what it was supposed to do which was allowed me to get some edge case LLM running on the machine. I ran ollama and I recommend going through Bijan Bowen tutorial online as he walks you through the initial setup and running the text based LLM. The jetson is too slow to run image generation LLM but you can give it a try. This is good starting point for getting into AI but I would recommend a real nvidia gpu if you want to play with the big boy LLMs. ... show more
Reviewed in the United States on June 9, 2026 by Van
    • 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
    • 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.
    • 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
    • Powerful Hardware, but a Frustrating and Fragmented User Experience
Style: Developer Kit
The NVIDIA Jetson Orin Nano Super is undeniably a powerhouse on paper, offering impressive AI throughput for edge computing. However, after integrating this into my workflow for mobile ALPR and custom security development, I’ve found that the actual user experience is marred by several design choices and technical hurdles that make it far from a "plug-and-play" professional tool. Installation and Hardware Ergonomics The physical layout of the board leaves much to be desired. The SD card slot location is remarkably inconvenient, especially if you have the board mounted in a custom enclosure or near other hardware. Furthermore, the complexity of getting the system to boot and run reliably from an NVMe drive is far higher than it should be in 2026. For a developer kit that essentially requires NVMe for any serious work, this process should be streamlined and native, rather than a multi-step technical hurdle that feels like a workaround. Stability Issues The most frustrating aspect has been the repeated system lockups. I’ve experienced multiple freezes during standard operation with no immediate or obvious cause. When you are trying to benchmark AI models or test long-term stability for a vehicle-mounted deployment, having the hardware randomly hang is a dealbreaker. It undermines the confidence you need in a board intended for "industrial" or "super" applications. Documentation and Support Fragmentation Finding clear, concise information is an uphill battle. NVIDIA’s documentation is scattered across too many different models and JetPack versions, making it incredibly difficult to find specific answers for the Orin Nano Super. You often find yourself digging through forum posts and outdated wiki pages to solve basic configuration issues. For a "Super" edition product, the support ecosystem feels fragmented and disorganized. What I Like: Raw Compute: When it is actually running, the CUDA performance is excellent for localized inference. Form Factor: It packs a lot of power into a small footprint, which is ideal for mobile security builds. What Needs Improvement: UI/UX for Setup: The NVMe boot process needs to be modernized and simplified. Reliability: Firmware or kernel stability needs to be addressed to stop the random lockups. Consolidated Documentation: A single, authoritative source of truth for this specific hardware would save developers hours of wasted time. Final Thoughts I like the potential of this product, and the hardware specs are exactly what I need for my security startup's infrastructure. However, the execution "leaves some to be had." If you aren't prepared to spend significant time troubleshooting and navigating a labyrinth of documentation, you might find the "Super" experience more frustrating than it’s worth. It’s a powerful tool, but it currently feels like it’s still in beta. ... show more
Reviewed in the United States on April 28, 2026 by Matthew VanDruff

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