Arduino UNO Q Development Board with Qualcomm QRB2210 Processor

Arduino
SKU: TH1869 MPN: ABX00162
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The Arduino UNO Q Development Board with Qualcomm® QRB2210 processor combines a quad-core Linux system and a real-time STM32 microcontroller on a single board.

Designed for AI, robotics, and IoT innovation, it features dual-band Wi-Fi 5, Bluetooth 5.1, USB-C DisplayPort output, and Arduino-compatible headers — making it ideal for edge computing and next-generation smart device prototyping.

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Overview

Arduino UNO Q is a hybrid single-board platform that fuses a Debian Linux application processor with a real-time microcontroller — giving you the performance of a small computer and the timing accuracy of an MCU on one UNO-form-factor board.

At its core, UNO Q pairs a quad-core Qualcomm® Dragonwing™ QRB2210 (Arm® Cortex®-A53, 2.0 GHz) with an STM32U585 (Arm® Cortex®-M33, up to 160 MHz). Linux apps and Arduino sketches communicate over Arduino Bridge (RPC), so you can run high-level AI/vision or web services on Linux while the MCU handles deterministic control for motors, sensors, and I/O.

Key Features & Benefits

  • Dual-core architecture: Combines a Linux-capable Qualcomm® Dragonwing™ processor with a real-time STM32U585 microcontroller for ultimate flexibility.
  • AI & Vision Ready: Built-in Adreno 702 GPU, dual ISPs, and MIPI-CSI/DSI interfaces for cameras and displays — ideal for edge AI and machine vision projects.
  • Seamless Development: Arduino App Lab lets you run Linux apps, Arduino sketches, and AI Bricks together from one environment.
  • Full Connectivity: Dual-band Wi-Fi® 5, Bluetooth® 5.1, and USB-C® with DisplayPort Alt-Mode.
  • Expandable Ecosystem: Standard Arduino UNO headers, Qwiic connector, and carrier board compatibility.
  • Robust Power Options: USB-C (5 V/3 A) or VIN (7–24 V) with built-in protection and smart power routing.
  • Modern Learning Platform: Perfect for education, prototyping, robotics, home automation, and edge computing.

Specification

Technical details for Arduino UNO Q Development Board with Qualcomm Dragonwing QRB2210 SoC.

Specification Details
Processor (MPU) Qualcomm® Dragonwing™ QRB2210 SoC — 4× Arm® Cortex®-A53 @ 2.0 GHz
GPU / Imaging Adreno 702 GPU @ ~845 MHz
Dual ISPs up to 13 MP+13 MP or 25 MP @ 30 fps
4-lane MIPI-CSI-2 camera
4-lane MIPI-DSI display.
Microcontroller (MCU) STMicroelectronics STM32U585 (Arm® Cortex®-M33 up to 160 MHz)
2 MB Flash & 786 kB SRAM
Memory / Storage LPDDR4X: 2 GB or 4 GB
eMMC: 16 GB or 32 GB (on-board).
Wireless Dual-band Wi-Fi® 802.11a/b/g/n/ac (Wi-Fi 5) + Bluetooth® 5.1 (Qualcomm WCN3980/WCBN3536A) with shared PCB antenna.
USB-C USB 3.1 with role switching
DisplayPort Alt-Mode (via ANX7625). PD contract: 5 V up to 3 A (no higher-voltage profiles).
When DP Alt-Mode is active, USB data rate may be reduced.
Headers & I/O JDIGITAL (3.3 V): SPI, I²C, UART, PWM, CAN; Arduino-style D0..D13 + extras.
JANALOG (3.3 V): A0..A5 (ADC); IOREF (3.3 V), 5V, 3V3, GND, VIN (7–24 V); analog pins not 5 V-tolerant.
Qwiic (3.3 V): I²C4_SDA/SCL for plug-and-play sensors/actuators.
JSPI (3.3 V): MOSI/MISO/SCK
JMEDIA (1.8 V + power): MIPI-CSI-2 / DSI, CCI I²C, camera clocks, VIN and 3V3 out.
JMISC (mixed): MCU PSSI/SDMMC/TRACE/I²C4, OPAMP1, audio IO, 1.8 V MPU GPIO, +5V_USB/+3V3/+1V8, VBAT, VCOIN.
JCTL (1.8 V): Console UART (SE4), boot/PMIC/reset control.
Analog ADC referenced to VREF+ ≈ 3.3 V
Valid input 0..VREF+
Absolute max ≈ VDD+0.3 V (~3.6 V).
Use dividers/buffers for higher voltages.
CAN FDCAN1 available on JDIGITAL pins (MCU domain, 3.3 V); external transceiver required.
Indicators 2× RGB LEDs (Linux-controlled)
2× RGB LEDs (MCU-controlled; active-low)
8×13 blue LED matrix.
Power LED (3.3 V rail).
Power Inputs USB-C 5 V (up to 3A PD) and VIN 7–24 V (on header)
Operating Conditions Voltage: USB-C 4.5–5.5 V; DC_IN 7–24 V.
Ambient: −10 °C to +60 °C (continuous).
Dimensions / Form Factor 68.58 mm × 53.34 mm
UNO-compatible outline, hole pattern, and stacking; bottom components ≤ ~2 mm for carrier clearance.
Software & Tools Debian Linux (MPU) + Arduino Core on Zephyr (MCU)
Arduino App Lab with “Bricks” for AI/web/integrations
Bridge RPC for Linux↔MCU.
Video Output DisplayPort Alt-Mode over USB-C (via ANX7625; source from MPU MIPI-DSI).
Camera MIPI-CSI-2 (4-lane) in 1.8 V domain; dedicated CCI I²C and MCLK lines (not general-purpose GPIO).
Power Button Long-press (≥5 s) reboots Linux (does not cut board power).
Variants ABX00162: 2 GB RAM / 16 GB eMMC;
ABX00173: 4 GB RAM / 32 GB eMMC.

Compare

Arduino UNO Q vs Raspberry Pi 5 vs Portenta H7 vs NVIDIA Jetson Orin Nano

Specification Arduino UNO Q Raspberry Pi 5 Arduino Portenta H7 NVIDIA Jetson Orin Nano
Processor Qualcomm® Dragonwing™ QRB2210 (4× Arm Cortex-A53 @ 2.0 GHz) Broadcom BCM2712 (4× Arm Cortex-A76 @ 2.4 GHz) ST STM32H747 (Cortex-M7 + Cortex-M4) 6-core Arm Cortex-A78AE + 1024-core Ampere GPU
Operating System Debian Linux + Zephyr (dual-OS) Raspberry Pi OS (Linux) Arduino Core + Mbed OS Ubuntu 20.04 + JetPack SDK
GPU Adreno 702 @ 845 MHz VideoCore VII @ 800 MHz None 1024-core Ampere GPU (Orin)
Memory / Storage 2 GB / 4 GB LPDDR4X + 16 GB / 32 GB eMMC 4 GB / 8 GB LPDDR4X + microSD 1 MB Flash + 1 MB RAM 8 GB LPDDR5 + eMMC 128 GB (optional)
Wireless Wi-Fi 5 (dual-band) + Bluetooth 5.1 Wi-Fi 5 + Bluetooth 5.0 Optional Wi-Fi / BLE Module Gigabit Ethernet / Wi-Fi (through dongle)
Video Output DisplayPort Alt-Mode via USB-C (DSI→DP) 2× micro HDMI (4K) None (uses external display modules) 1× HDMI 2.1 + MIPI DSI
I/O Voltage 1.8 V (MPU) + 3.3 V (MCU) 3.3 V logic 3.3 V logic 1.8 V / 3.3 V mixed
Typical Use Case AI + Real-time control (dual processor) General Linux computing and education Industrial IoT and embedded control Edge AI and robot vision projects
Power Input USB-C 5 V (3 A) / VIN 7–24 V USB-C 5 V (5 A) VIN 5–18 V / USB-C 5 V Barrel Jack 19 V / USB-C PD
Form Factor Arduino UNO (68.6 × 53.3 mm) Credit card (85 × 56 mm) Portenta (66 × 25 mm) Developer Kit (100 × 79 mm)
Ideal For Edge AI education, robotics, IoT with Linux + MCU Hobby projects and general Linux use Industrial control and prototyping High-performance AI inference and vision

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