NVIDIA Jetson Nano Developer Kit-B01
Join the Revolution and Bring the Power of AI to Millions of Devices.
The NVIDIA® Jetson Nano™ Developer Kit delivers the compute performance to run modern AI workloads at an unprecedented size, power, and cost. Developers, learners, and makers can now run AI frameworks and models for applications like image classification, object detection, segmentation, and speech processing.
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PRODUCT DETAILS
Description
The NVIDIA® Jetson Nano™ Developer Kit delivers the compute performance to run modern AI workloads at an unprecedented size, power, and cost. Developers, learners, and makers can now run AI frameworks and models for applications like image classification, object detection, segmentation, and speech processing.
The developer kit can be powered by micro-USB and comes with extensive I/Os, ranging from GPIO to CSI. This makes it simple for developers to connect a diverse set of new sensors to enable a variety of AI applications. It’s incredibly power-efficient, consuming as little as 5 watts.
Jetson Nano is also supported by NVIDIA JetPack, which includes a board support package (BSP), Linux OS, NVIDIA CUDA®, cuDNN, and TensorRT™ software libraries for deep learning, computer vision, GPU computing, multimedia processing, and much more. The software is even available using an easy-to-flash SD card image, making it fast and easy to get started.
The same JetPack SDK is used across the entire NVIDIA Jetson™ family of products and is fully compatible with NVIDIA’s world-leading AI platform for training and deploying AI software. This proven software stack reduces complexity and overall effort for developers.
Note
Please pay attention and follow the steps below to insert/remove an SD card.
Inserting an SD card: Slightly push the SD card into the card slot until you hear a click sound. If you hear that sound, that means the SD card has been successfully inserted.
Removing an SD card: Slight push the SD card inside the card slot until you hear a click sound. Then release it and the SD card will automatically pop out.
Key Features
Jetson Nano Module
- 128-core NVIDIA Maxwell™ GPU
- Quad-core ARM® A57 CPU
- 4 GB 64-bit LPDDR4
- 10/100/1000BASE-T Ethernet
Power Options
- Micro-USB 5V 2A
- DC power adapter 5V 4A
I/O
- USB 3.0 Type A
- USB 2.0 Micro-B
- HDMI/DisplayPort
- M.2 Key E
- Gigabit Ethernet
- GPIOs, I2C, I2S, SPI, UART
- MIPI-CSI camera connector
- Fan connector
- PoE connector
Kit Contents
- NVIDIA Jetson Nano module and carrier board
- Quick Start Guide and Support Guide
Changes with the B01 Kit
| 114992260 | 114992261 | 114992262 | 114992263 | 114992264 | 114992265 | 114992270 | |
|---|---|---|---|---|---|---|---|
| Diagonal Field of View (FOV) | 77° | 77° | 130° | 160° | 160° | 200° | 83° |
| IR LED Modules | None | 2 | None | None | 2 | None | None |
| Aperture | 2.0 | 2.0 | 1.8 | 2.35 | 2.35 | 2.0 | / |
| Focal Length | 2.96mm | 2.96mm | 1.88mm | 3.15mm | 3.15mm | 0.87mm | 2.6mm |
| Lens Construction | 4P | 4P | 4E+IR | 6G+IR | 6G+IR | 1G4P+IR | / |
| Distortion | <1% | <1% | <7.6% | <14.3% | <14.3% | <18.6% | <1% |
| EFL | 2.93mm | 2.93mm | 1.85mm | 3.15mm | 3.15mm | 0.9mm | / |
| BFL (Optical) | 1.16mm | 1.16mm | 1.95mm | 3.15mm | 3.15mm | 1.41mm | / |
Reinforce Your Projects with Grove Pi HAT
If you want to use Grove sensors with Jetson Nano, grab the grove.py Python library and get your sensors up in running in minutes! Currently, there are more than 20 Grove modules supported on Jetson Nano and we will keep adding more. You can connect Grove modules using Base HAT for Raspberry Pi or Raspberry Pi Zero with Jetson Nano.
Note
We provide a wide selection of AI-related products including Machine Learning, Computer Vision, Edge Computing, Speech Recognition & NLP and Neural Networks Acceleration. Check here for more products you may need.
We are also calling for feedback and inputs from the developers. Any suggestions on the product features are welcomed at Seeed Forum!
Specifications
- GPU: 128-core Maxwell
- CPU:Quad-core ARM A57 @ 1.43 GHz
- Memory: 4 GB 64-bit LPDDR4 25.6 GB/s
- Storage: microSD (not included)
- Video Encoder: 4K @ 30 | 4x 1080p @ 30 | 9x 720p @ 30 (H.264/H.265)
- Video Decoder: 4K @ 60 | 2x 4K @ 30 | 8x 1080p @ 30 | 18x 720p @ 30|(H.264/H.265)
- Camera: 2x MIPI CSI-2 DPHY lanes
- Connectivity: Gigabit Ethernet, M.2 Key E
- Display: HDMI 2.0 and eDP 1.4
- USB: 4x USB 3.0, USB 2.0 Micro-B
- Others: GPIO, I2C, I2S, SPI, UART
- Mechanical: 100 mm x 80 mm x 29 mm
Version Change Information for B01 from A02
- The B01 revision carrier is compatible with the production specification Jetson Nano module. The A02 revision carrier is not.
- Removed Button Header [J40] Position
- Removed Serial Port Header [J44] Position
- Adjusted the Position of Power Select Jumper [J48]
- Adjusted the Position of Camera Connector [J13]
- Added Camera Connector [J49] location
- Factory JetPack Upgrade from 4.2 SDK to 4.3 SDK
Note
If you are looking for open source SBC for commercial and industrial needs. Seeed provides customization service based on BeagleBone series boards. Seeed Studio BeagleBone® Green(BBG) and Seeed Studio BeagleBone® Green Wireless (BBGW) provide more stable industrial deployment scenarios.
ECCN/HTS
| HSCODE | 8543709990 |
| USHSCODE | 8517620090 |
| UPC |
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REVIEWS
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Great little computerEverything is good, you can use it to do many things, I love it especially for machine learning.
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An authentic Jetson NanoVery sufficient use of resources, instead of deploying a big rig, this provides just the right amount of power and resources for personal projects.
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Excellent product.It just gives you confidence that everything Nvidia makes is great. General purpose GPU programmatically compatible with top-of-the-line GPUs. Wonderful for learning, prototyping and even development.
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Nearly unbelievable value for about $100I have worked with many SBCs. This is by far my favorite in this price range.
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This is an absolute bargain for the price.It is nice option to be able to insert Wi-Fi adapter. So we can use Wi-Fi 6 now and don't wait for a hardware updates.
Nvidia community is very friendly and helpful but linux kernel updates is not often for now.
Latest kernel version is 4.9 version, so if you need kernel 5 you will have to wait for updates.