NVIDIA Jetson Orin Nano Super Developer Kit
by NVIDIA
- The NVIDIA Jetson Orin Nano Super Developer Kit is a compact, 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 run vision transformers, large language models, and more. This affordable and accessible platform is supported by NVIDIA AI software and a broad ecosystem. Existing users can upgrade with just a software update, unlocking new possibilities in 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.
Our Experience
As someone constantly juggling multiple projects, I needed a powerful, portable AI solution for my edge devices. Enter NVIDIA Jetson Orin Nano Super Developer Kit. This tiny powerhouse has been a game-changer. Right off the bat, it's impressively compact yet packs a punch. It arrived just in time to accelerate my generative AI project, and I was blown away by its performance. The 8GB module coupled with the reference carrier board made setup a breeze. NVIDIA's AI software stack is intuitive, making it easy for me to dive right into developing use-case-specific applications. Two things stood out: first, the seamless integration of NVIDIA Isaac for robotics and Metropo for smart cities. These frameworks have significantly sped up my workflows. Secondly, the extensive ecosystem of partners offering tools and software customization options has been invaluable.
Customer Reviews
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 n
Slight pain on getting newer jetpack installed for non-Linux person, but i got it. I had Ollama Phi3 up and running very quickly I'm impressed and looking forward to playing with it more.
Nice, inexpensive SBC to run small AI models. Using with Karakeep and Home Assistant for lightweight AI tasks. The 8GB of RAM limits you to using models 7 billion parameters or less.
Two things to consider:1. If you put the board into a case you have to change the antenna wires, which is problematic. I could not get the new antenna wires to go into the very small plugs, and after failing couldn't get the plate antenna plugs back in. Yes, i likely bent something but these plugs are really small.2. Due to LLM sizes the 8G memory footprint has limited use. There are several use cases where 8G works but not as many as you would think.
what a waste of time, not worth my sanity. another day and I'd likely take a sledge hammer to it.nvidia software, their os, the sdk, the code examples (jetson lab), all of it is just absolute garbage.first, you must have real computer (vm won't do) with intel and ubuntu 22.04 just to flash the nvme.then you find out nothing works. first clue was their "readme" link they placed on the desktop "for my convience", which doesn't work, points to nothing. snap needs downgrading before you can run any
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