- Compact size Jetson Xavier NX module powerful enough for advanced AI applications with low power consumption
- Supports Entire NVIDIA Software Stack for application development and optimization
- Rich I/O Peripherals to further expand AI projects
- Onboard Fan to provide better heat dissipation
- More than 10X the performance of Jetson TX2
- Enables development of AI applications using NVIDIA JetPack™ SDK
- Easy to build, deploy, and manage AI at the edge
- Flexible and scalable platform to get to market with reduced development costs
- Continuous updates over the lifetime of the product
- Compatible with Nimbus: connect your ROS project to the cloud
The NVIDIA® Jetson Xavier™ NX Developer Kit brings supercomputer performance to the edge. It includes a power-efﬁcient, compact Jetson Xavier NX module for AI edge devices. It beneﬁts from new cloud-native support and accelerates the NVIDIA software stack in as little as 10 W with more than 10X the performance of its widely adopted predecessor, Jetson TX2. The capability to develop and test power-efﬁcient, small form-factor solutions with accurate, multi-modal AI inference opens the door for new breakthrough products.
Developers can now take advantage of cloud-native support, transforming the experience of developing and deploying AI software to edge devices. Pre-trained AI models from NVIDIA NGC, together with the NVIDIA Transfer Learning Toolkit, give a faster path to trained and optimized AI networks. Containerized deployment to Jetson devices also allows flexible and seamless updates.
The developer kit is supported by the entire NVIDIA software stack, including accelerated SDKs and the latest NVIDIA tools for application development and optimization. When combined with the compact Jetson Xavier NX, this powerful stack helps you create innovative solutions for smart cities, retail, manufacturing, logistics, healthcare, agriculture, and more.
Designed for ease of use and speed of deployment, Jetson is the most flexible platform to get to market and continuously update over the lifetime of a product.
Don't forget to explore the blog Bringing Cloud-Native Agility to Edge AI Devices with the NVIDIA Jetson Xavier NX Developer Kit by the NVIDIA team.
To learn more about Jetson Xavier, please visit the Jetson Xavier NX Technical Blog with Benchmarks, also by the NVIDIA team.
This product has shipping restriction to certain countries. It can’t be sent to countries and regions listed as below: NORTH KOREA, CUBA,IRAN (ISLAMIC REPUBLIC OF), LIBYA, SYRIA, UKRAINE, SUDAN.
Bringing Cloud-Native Agility to Edge AI Devices with the NVIDIA Jetson Xavier NX Developer Kit
Comparison Between The NVIDIA Jetson AI Developer Kits
|Jetson Nano Developer Kit||Jetson TX2 Developer Kit||Jetson Xavier NX|
|Jetson AGX Xavier Developer Kit|
|AI Performance||0.5 TFLOPS (FP16)||1.3 TFLOPS (FP16)||6 TFLOPS (FP16)
21 TOPS (INT8)
|5.5-11 TFLOPS (FP16)
20-32 TOPS (INT8)
|GPU||128-core NVIDIA Maxwell™ GPU||256-core NVIDIA Pascal™ GPU architecture with 256 NVIDIA CUDA cores||NVIDIA Volta architecture with 384 NVIDIA CUDA® cores and 48 Tensor cores||512-Core Volta GPU with Tensor Cores|
|CPU||Quad-core ARM A57 @ 1.43 GHz||Dual-Core NVIDIA Denver 2 64-Bit CPU
Quad-Core ARM® Cortex®-A57 MPCore
|6-core NVIDIA Carmel ARM®v8.2 64-bit CPU 6 MB L2 + 4 MB L3||8-Core ARM v8.2 64-Bit CPU, 8 MB L2 + 4 MB L3|
|Memory||4 GB 64-bit LPDDR4 25.6 GB/s||8GB 128-bit LPDDR4
1866 MHz - 59.7 GB/s
|8 GB 128-bit LPDDR4x @ 51.2GB/s||32 GB 256-Bit LPDDR4x | 137 GB/s|
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 welcome at Seeed Forum!
You can head over to NVIDIA Jetson Download Center to explore the necessary drivers and software for this product.
|GPU||NVIDIA Volta architecture with 384 NVIDIA CUDA® cores and 48 Tensor cores|
|CPU||6-core NVIDIA Carmel ARM®v8.2 64-bit CPU 6 MB L2 + 4 MB L3|
|DL Accelerator||2x NVDLA Engines|
|Vision Accelerator||7-Way VLIW Vision Processor|
|Memory||8 GB 128-bit LPDDR4x @ 51.2GB/s|
|Storage||microSD (Card not included)|
|Video Encode||2x 4K @ 30 | 6x 1080p @ 60 | 14x 1080p @ 30 (H.265/H.264)|
|Video Decoder||2x 4K @ 60 | 4x 4K @ 30 | 12x 1080p @ 60 | 32x 1080p @ 30 (H.265)|
|2x 4K @ 30 | 6x 1080p @ 60 |16x 1080p @ 30 (H.264)|
|Camera||2x MIPI CSI-2 D-PHY lanes|
|Display||HDMI and DP|
|Connectivity||10/100/1000 Base-T Gigabit Ethernet|
|M.2 Key E (WiFi/BT included)|
|M.2 Key M (NVMe)|
|I/O||4x USB 3.1 Gen2 Type A|
|USB 2.0 Micro-B|
|40-pin header (GPIOs, I2C, I2S, SPI, UART)|
|2x MIPI-CSI camera connector|
|Interfaces||GPIOs, I2C, I2S,SPI, UART|
|Power Supply||DC Jack (9V - 19V)|
|Dimensions||103 mm x 90.5 mm x 31 mm|
- 1 x NVIDIA® Jetson Xavier™ NX Module
- 1 x Reference Carrier Board
- 1 x Quick Start Guide
- 1 x Support Guide
- 1 x Power Adapter: AC power brick with power cord
LEARN AND DOCUMENTS
SHARED BY USERS
Amazing productt!!!Got this nice guy! Finally I can do some cool projects with it. I worked with Arduino before. This should be a new field of RC car project. Hope it works well.
Game changer SBCThis works very well for computer vision. The documentation provided on the nvidia githib is very good and can get you set up fast.
olid for AI studyNvidia provides an impressive dev board for delving into AI at an affordable price. The only drawback I see with this dev board unlike others that are available is that is does not include onboard wifi, bluetooth or audio. However, you can get usb dongles to remedy that very easily.
Excellent product. It just gives you confidence that everything Nvidia makes is great.Great tutorials. Plenty of memory and processing power. General purpose GPU programmatically compatible with top-of-the-line GPUs. Wonderful for learning, prototyping and even development.
Powerful tool for machine learning applications.Powerful tool for machine learning applications. Easy setup (compared to TX2) and lots of choices for projects. Use a fast (Samsung EVO or Pro) microsd.
Note that there are some small differences between old and new versions for mounting options and add-on hardware.