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Arduino VENTUNO™ Q Edge AI Single Board Computer - Coming Soon

Arduino VENTUNO™ Q Edge Artificial Intelligence (AI) Single Board Computer (SBC) is a high‑performance development platform designed to bring AI directly into real‑world, physical applications such as robotics, vision systems, and intelligent automation. Built around a powerful dual‑brain architecture, it combines a Qualcomm Dragonwing™ IQ8 AI processor for advanced neural network inference with an STM32H5 microcontroller dedicated to deterministic, real‑time control, enabling perception, decision‑making, and action to coexist on a single board. The Arduino VENTUNO Q supports demanding edge AI workloads with integrated NPU, CPU, and GPU resources while maintaining sub‑millisecond responsiveness for motion control and industrial I/O.

The board offers a unified development experience through Arduino App Lab, allowing developers to work seamlessly with Arduino sketches, Python, Linux applications, and AI models in one environment, whether used as a standalone Linux desktop or connected to a host PC. With support for multiple cameras, high‑speed connectivity, and a rich ecosystem of optimized, ready‑to‑run AI models, VENTUNO Q empowers developers to build fully offline, low‑latency intelligent systems that can see, understand, and interact with the physical world without relying on cloud computing.

Features

  • Accelerated dual-brain architecture, which communicates seamlessly via RPC (Remote Procedure Call) bridge for real-world AI
    • AI brain - Dragonwing IQ-8275 processor delivers NPU, CPU, and GPU for complex neural network inference
    • Action brain - STM32H5F5 microcontroller enables sub-millisecond response to guarantee stable, deterministic control for robotics, motion systems, and industrial interfaces
  • 2x setup modes for a unique experience
    • SBC
      • Add a monitor, keyboard, and mouse
      • Users will have a professional Linux desktop with the Arduino App Lab ready to launch
    • PC-based set-up - connect VENTUNO Q to a laptop or desktop computer via USB Type-C® or network connection to run Arduino App Lab on a PC
  • High-bandwidth 16GB RAM enables concurrent multi-model AI inference
  • 64GB expandable storage - industrial-grade eMMC plus M.2 connector for NVMe Gen 4 storage expansion
  • 3x 4-lane MIPI-CSI camera interfaces for 360° awareness, stereo depth perception, and multi-angle inspection
  • Display outputs
    • MIPI-DSI for touchscreens and interactive panels
    • HDMI for monitors and projectors
    • USB Type-C DisplayPort Alt Mode for versatile video output
  • Tri-band Wi-Fi® 6 (2.4/5/6GHz) and BLUETOOTH® 5.3 for wireless connectivity, 2.5Gb Ethernet
  • Universal USB connectivity
    • USB Type-C for high-speed vision and audio data transfer
    • Dual USB-A 3.0 ports for peripherals and storage
  • Industrial I/O and control
    • CAN-FD for professional motor controllers and industrial networks
    • PWM and deterministic GPIO for sub-millisecond response
  • Purpose-built for robotics and physical actuation
    • Supports Robot Operating System 2 (ROS 2) for advanced, real-time robot development
    • Arduino App Lab includes specific robotics Bricks that bundle complex functionality into accessible, reusable components
    • Instant responses on GPIO, PWM, and CAN-FD enable zero-jitter motor control and safety-critical reliability
  • Unmatched hardware compatibility for rapid innovation
    • Arduino UNO™ shields support - native compatibility with all UNO shields, motor controllers, sensors, displays, and wireless interfaces work out of the box
    • Raspberry Pi® Hat compatibility - standard 40-pin GPIO header provides full electrical and mechanical compatibility with Raspberry Pi accessories
    • Arduino Modulino™ nodes and Qwiic connectivity - solder-free Qwiic connector supports chainable Modulino nodes and hundreds of Qwiic-compatible sensors with polarized, error-proof connections
    • High-speed media carrier support - advanced carrier headers (JMEDIA, JOMEGA, JMISC) provide dedicated lanes for high-speed cameras, displays, multi-axis control, and sensor fusion
  • Versatile, ready-to-run AI models
    • Local LLMs - use Qwen for sophisticated natural language understanding entirely on-device, without cloud dependencies or data transmission
    • Local VLMs - Qwen VLM combines visual perception with natural language understanding for image captioning, scene description, OCR, and more
    • TTS and ASR - leverage Melo TTS and Whisper, which allow offline devices to understand natural speech, transcribe, and give human-like responses
    • Gesture recognition - recognize hand gestures, finger movements, and sign language for touchless interfaces and human-robot interaction using MediaPipe
    • Object tracking - use YOLO-X (You Only Look Once - eXtended) to track people, vehicles, or objects in real-time across multiple camera views
    • Pose detection - track body pose, joint positions, and movement patterns with PoseNet (for fitness applications, safety monitoring, and interactive gaming)

Applications

  • Robotics and motion control
  • AI-powered systems
  • Edge AI vision and sensing systems
  • Education and research

Specifications

  • Qualcomm Dragonwing IQ8 (IQ-8275) microprocessor (MPU)
    • Octa-core Arm® Cortex® CPU
    • Arm Cortex A623 Adreno GPU/VPU at 877MHz
    • Hexagon Tensor AI Processor (NPU) with up to 40 dense TOPS
    • Qualcomm Spectra 692 ISP
    • Ubuntu or Debian upstream operating system (OS)
  • STM32H5F5 microcontroller (MCU)
    • Arm Cortex M33 at 250MHz
    • 4MB flash
    • 1.5MB RAM
    • Arduino core on Zephyr OS
  • 16GB LPDDR5 RAM
  • Storage
    • 64GB eMMC
    • M.2 connector for NVME Gen 4 external storage
  • Connectivity
    • Wi-Fi 6 2.4/5/6GHz with onboard antenna
    • Bluetooth 5.3 with onboard antenna
    • 1x 2.5Gbit RJ45
  • Camera
    • USB camera support
    • 3x MIPI CSI connectors muxed with 2x MIPI CSI on JMEDIA header
  • Video
    • 1x HDMI muxed with MIPI DSI on JMEDIA header
    • Video output (DP Alt mode) support via USB Type-C
    • MIPI DSI pins on JMEDIA header
  • 2x Microphone IN / Headphone OUT / Ear OUT / Line OUT on JMISC header for audio
  • Power supply
    • 5VDC maximum at 3A from the USB Type-C connector
    • 5.5mm x 2.1mm power jack, 12VDC to 24VDC
    • 7VDC to 24VDC screw terminal
    • 7V to 24V on JOMEGA
  • USB
    • 1x USB Type-C port with host/device role switching, power role switch, and video output
    • 2x USB 3.0 Type A
    • 2x USB 3.0 on JOMEGA header
  • CAN
    • 1x CAN-FD PHY on screw terminal
    • 3x CAN-FD (no PHY) on JOMEGA header
    • 1x CAN-FD (no PHY) on UNO Shield headers
  • 160mm x 100mm x 25.8mm size
发布日期: 2026-03-17 | 更新日期: 2026-03-18