AN110-XNXEdge AI board with an NVIDIA Jetson Xavier NX module
- Manufacturer
- Configurations
- 3 available configurations
AN110-XNX is a compact Aetina edge AI platform, conceived to bring inference and data pre-processing inside machines and already crowded cabinets.
The Jetson Xavier NX module brings a 6-core NVIDIA Carmel Arm CPU with LPDDR4x memory. The assembly weighs 0.14 kg and declares a module power draw between 1.098 and 17.061 W.
At a glance
- AI module: NVIDIA Jetson Xavier NX
- AI performance: 14 TOPS @10W
- CPU class: ARM Carmel
- Processor: 6-core NVIDIA Carmel ARM®v8.2 64-bit CPU 6MB L2 + 4MB L3
- Memory: 8 GB 128-bit LPDDR4x
Technical specifications
| AI module | NVIDIA Jetson Xavier NX |
|---|---|
| AI performance | 14 TOPS @10W21 TOPS @15W |
| CPU class | ARM Carmel |
| Processor | 6-core NVIDIA Carmel ARM®v8.2 64-bit CPU 6MB L2 + 4MB L3 |
| Graphics | 384 CUDA cores and 48 Tensor cores |
| Tensor cores | 48 |
| CUDA cores | 384 |
| Memory | 8 GB 128-bit LPDDR4x |
|---|---|
| RAM type | LPDDR4x |
| Storage | 16 GB eMMC 5.1 |
|---|
| Video outputs | 1× eDP1× HDMI (Type-A) |
|---|
| Ethernet ports | 1× GbE (RJ-45) |
|---|---|
| USB ports | 1× USB 2.0 (Micro-AB), solo OTG2× USB 3.2 Gen1 (Type-A) |
| Serial interfaces | 1× RS-232 |
| Audio | HDMI Integrated |
| Digital I/O | 5× GPIO(bidir) |
| Expansion | 1× M.2 E-Key 2230 (PCIe/USB2.0) |
|---|
| AC/DC input | DC |
|---|---|
| Power input | DC V |
| Power consumption | 1.098–17.061 W |
| Dimensions | 87.4 × 28.7 × 67.4 mm |
|---|---|
| Weight | 0.14 kg |
| Operating temperature | -20–55 °C |
|---|---|
| Storage temperature | -40–85 °C |
| Certifications | FCCCE |
|---|
| Operating systems | Linux |
|---|
Data extracted from the manufacturers' technical sheets: the official product spec sheet remains the reference for final confirmation.
Family configurations
The order codes of this family: the sheet applies to all of them, the detail of each configuration is in the datasheet.
| Configuration (PN) |
|---|
| AN110-XNX-EN03 |
| AN110-XNX-EN70 |
| AN110-XNX-FN01 |
Documentation
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