
Nvidia Jetson
Edge AI solutions with Nvidia Jetson family
Following the global technology trends, we are aiming for bringing AI to the edge. To do this, we collaborate with the best – Nvidia has already created a golden standard for on-device AI with its Jetson product family.
Using high-performance & energy-efficient Nvidia Jetson Nano, Jetson TX2, Jetson Xavier NX, or Jetson AGX Xavier AI computing platforms in FPGA programming projects, we provide premier hardware design services.
About Nvidia Jetson
Nvidia Jetson products are great embedded solutions that are scalable and power-efficient. Each system represents a comprehensive SoM (System-on-Module), containing a CPU, GPU, DRAM, flash storage, and PMIC.
The whole product family has a common software stack, which adds to easy and widespread deployment. Nvidia provides Jetson platforms with the same Jetpack SDK, including BSP (board support package), Linux OS, and Nvidia CUDA. It is compatible with 3rd-party platforms.

Our services
We offer a range of development services using NVIDIA Jetson platforms: from custom software/hardware design to turnkey product development, whether for startups, niche companies, market leaders or enterprises.
Electronic hardware design on Jetson
Power & performance optimization
ML/DL algorithms deployment
Audio & Video
Firmware & BSP development
Mobile & Cloud apps development
Edge AI solutions application areas
Smart Surveillance
Industrial robotics
Audio analytics
Predictive maintenance
Body monitoring
Autonomous vehicles
Face recognition
Expression analysis
Nvidia Jetson module specification comparison
Jetson Nano | Jetson TX2 Series | Jetson Xavier NX | Jetson AGX Xavier | |||
TX2 NX | TX2 4GB | TX2 | TX2i | |||
472 GFLOPS | 1.33 TFLOPS | 1.26 TFLOPS | 21 TOPS | 32 TOPS | ||
128-core NVIDIA Maxwell™ GPU | 256-core NVIDIA Pascal™ GPU | 384-core NVIDIA Volta™ GPU with 48 Tensor Cores | 512-core NVIDIA Volta™ GPU with 64 Tensor Cores | |||
Quad-core ARM®Cortex®-A57MPCore processor | Dual-core Denver 2 64-bit CPU and quad-core Arm® Cortex®-A57 MPCore processor | 6-core NVIDIA Carmel ARM®v8.2 64-bit CPU 6MB L2 + 4MB L3 | 8-core NVIDIA Carmel Arm®v8.2 64-bit CPU 8MB L2 + 4MB L3 | |||
4 GB 64-bitLPDDR4 25.6GB/s | 4 GB 128-bit LPDDR4 51.2GB/s | 8 GB 128-bitLPDDR4 59.7GB/s | 8 GB 128-bitLPDDR4 (ECC Support) 51.2GB/s | 8 GB 128-bit LPDDR4x 51.2GB/s | 32 GB 256-bitLPDDR4x 136.5GB/s | |
16 GB eMMC 5.1 | 16 GB eMMC 5.1 | 32 GB eMMC 5.1 | 32 GB eMMC 5.1 | 16 GB eMMC 5.1 | 32GB eMMC 5.1 | |
5W | 10W | 7.5W | 15W | 10W | 20W | 10W | 15W | 10W | 15W | 30W | ||
1 x4 (PCIe Gen2) | 1 x1 + 1 x2 (PCIe Gen2) | 1 x1 + 1 x4 OR 1 x1 + 1 x1 + 1 x2 (PCIe Gen2) | 1 x1 (PCIe Gen3) + 1 x4 (PCIe Gen4)* | 1 x8 + 1 x4 + 1 x2 + 2 x1 (PCIe Gen4, Root Port & Endpoint) | ||
Up to 4 cameras 12 lanes MIPI CSI-2 D-PHY 1.1 (up to 18 Gbps) | Up to 5 cameras (12 via virtual channels) 12 lanes MIPI CSI-2 D-PHY 1.2 (up to 30 Gbps) | Up to 6 cameras (12 via virtual channels) 12 lanes MIPI CSI-2 D-PHY 1.2 (up to 30 Gbps) | Up to 6 cameras (24 via virtual channels) 14 lanes MIPI CSI-2 D-PHY 1.2 (up to 30 Gbps) | Up to 6 cameras (36 via virtual channels) 16 lanes MIPI CSI-2 | 8 lanes SLVS-EC D-PHY 1.2 (up to 40 Gbps) C-PHY 1.1 (up to 91 Gbps) | ||
1x 4K30 (H.265) 2x 1080p60 (H.265) | 1x 4K60 (H.265) 3x 4K30 (H.265) 4x 1080p60 (H.265) | 2x 4K30 (H.265) 6x 1080p60 (H.265) | 4x 4K60 (H.265) 16x 1080p60 (H.265) 32x 1080p30 (H.265) | |||
1x 4K60 (H.265) 4x 1080p60 (H.265) | 2x 4K60 (H.265) 7x 1080p60 (H.265) 14x 1080p30 (H.265) | 2x 4K60 (H.265) 12x 1080p60 (H.265) 16x 1080p30 (H.265) | 2x 8K30 (H.265) 6x 4K60 (H.265) 26x 1080p60 (H.265) 72x 1080p30 (H.265) | |||
2 multi-mode DP 1.2/eDP 1.4/HDMI 2.0 1 x2 DSI (1.5Gbps/lane) | 2 multi-mode DP 1.2/eDP 1.4/HDMI 2.0 1x 2 DSI (1.5Gbps/lane) | 2 multi-mode DP 1.2/eDP 1.4/HDMI 2.0 2 x4 DSI (1.5Gbps/lane) | 2 multi-mode DP 1.4/eDP 1.4/HDMI 2.0 No DSI support | 3 multi-mode DP 1.4/eDP 1.4/HDMI 2.0 No DSI support | ||
- | - | 2x NVDLA Engines | 2x NVDLA Engines | |||
- | - | 7-Way VLIW Vision Processor | 7-Way VLIW Vision Processor | |||
10/100/1000 BASE-T Ethernet | 10/100/1000 BASE-T Ethernet | 10/100/1000 BASE-T Ethernet, WLAN | 10/100/1000 BASE-T Ethernet | 10/100/1000 BASE-T Ethernet | 10/100/1000 BASE-T Ethernet | |
69.6 mm x 45 mm 260-pin SO-DIMM connector | 69.6 mm x 45 mm 260-pin SO-DIMM connector | 87 mm x 50 mm 400-pin connector | 69.6 mm x 45 mm 260-pin SO-DIMM connector | 100 mm x87 mm 699-pin connector |
Our tech map in FPGA
Software platforms
Xilinx Deep Neural Network (xDNN), Xilinx Alveo, Intel OpenVINO Toolkit, TensorFlow, Keras, Caffe
Tools & Languages
C++, Python, Matlab/Simulink, Verilog, VHDL, HLS, DSP, AI toolboxes
Specialized tools
Xilinx Vitis AI, Xilinx Vivado Design Suite, Intel Quartus Prime, SDAccel, SDSoC, HDL Coder
Hardware design
High-speed interfaces, DDR4, JESD204b, SI, PI, thermo modelling, video processing
Platforms
Zynq, Zynq US+, RF SoC, Xilinx Versal, FPGA
Tranceivers
AD9361, AD9371, ADRV9009, radars, Promwad AFE, antenas
Network software
DPDK, UDP 10G, TCP 10G, TAPs, L1/L2 IP cores
Communications
PCI-e, 1G, 10G, 25G/40G, 100G
Our FPGA design projects
Do you need a quote for your Edge AI project?
Drop us a line about your project! We will contact you today or the next business day. All submitted information will be kept confidential.