Where AI Takes Action
The Dragonwing IQ-8275 processor delivers NPU, CPU, and GPU for complex neural network inference.
The STM32H5F5 microcontroller enables sub-millisecond response to guarantee stable, deterministic control for robotics, motion systems, and industrial interfaces.
Develop Arduino sketches, Python scripts, and AI models in one consistent environment. Arduino App Lab seamlessly bridges embedded programming, Linux development, and edge AI, giving you a single environment for your entire application stack.
Accelerate development with a wide range of AI models optimized for the integrated NPU of VENTUNO Q – or customize for your unique challenges! Powered by Edge Impulse and Qualcomm® AI Hub, this is your gateway to extensive AI libraries.
Use Qwen for sophisticated natural language understanding entirely on-device, without cloud dependencies or data transmission.
Qwen VLM combines visual perception with natural language understanding for image captioning, scene description, OCR, and more.
Leverage Melo TTS and Whisper, allow offline devices to understand natural speech, transcribe, and give human-like responses.
Recognize hand gestures, finger movements, and sign language for touchless interfaces and human-robot interaction using MediaPipe.
Use YOLO-X (You Only Look Once - eXtended) to track people, vehicles, or objects in real-time across multiple camera views.
Track body pose, joint positions, and movement patterns with PoseNet. For fitness applications, safety monitoring, and interactive gaming.
VENTUNO Q is engineered specifically for systems that move, manipulate, and respond to the physical world with precision and reliability.
- ROS 2 Compatibility
VENTUNO Q supports ROS 2 (Robot Operating System 2) for advanced, real-time robot development. - Robotics Bricks in Arduino App Lab
Arduino App Lab includes specific robotics Bricks that bundle complex functionality into accessible, reusable components. - Real-time motion control excellence
Instant response on GPIO, PWM, and CAN-FD enables zero-jitter motor control and safety-critical reliability.
| Componente | Specifiche |
|---|---|
| Microprocessor (MPU) | Qualcomm Dragonwing™ IQ8 (IQ-8275): • CPU: 8-core Qualcomm® Kryo™ • GPU: Qualcomm® Adreno™ 623 • NPU: Qualcomm® Hexagon™ 40 dense TOPS • Qualcomm Spectra 692 ISP OS: Ubuntu or Debian upstream |
| Microcontroller (MCU) | STM32H5F5: • Arm® Cortex® M33 at 250MHz • 4MB flash • 1.5MB RAM OS: Arduino core on Zephyr |
| RAM | 16GB LPDDR5 |
| Storage | • 64GB eMMC • M.2 connector for NVME Gen.4 external storage |
| Connectivity | • Wi-Fi® 6 2.4/5/6 GHz 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-C • MIPI DSI pins on JMEDIA header |
| Audio | 2x Microphone IN / Headphone OUT / Ear OUT / Line OUT on JMISC header |
| Power Supply | • From USB-C connector 5 VDC max at 3 A • 5.5x2.1 mm Power Jack 12-24 VDC • Screw Terminal 7-24 VDC • 7-24 V on JOMEGA |
| USB | • 1x USB-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 |
| Dimensions | • 160x100x25.8 mm |
VENTUNO Q brings together up to 40 dense TOPS of AI compute with a dedicated real-time microcontroller in a unified dual-brain architecture. While competitors focus purely on AI inference, VENTUNO Q delivers both intelligence and deterministic actuation – essential for robotics, industrial control, and any application where AI must interact with the physical world. Arduino App Lab provides an accessible development experience that scales from beginner to professional level, while unmatched ecosystem compatibility (UNO shields, UNO carriers, Raspberry Pi Hats, Modulino nodes) accelerates prototyping.
Both options are fully supported. While Arduino App Lab streamlines AI and robotics development, VENTUNO Q itself is a complete Ubuntu/Debian Linux system. You can use standard IDEs such as VS Code, PyCharm, Eclipse, Vim, Emacs, Python virtual environments and package managers, Docker containers for isolated environments, SSH remote development and headless operation. Any framework or toolchain you prefer! App Lab accelerates development but never restricts your workflow.
VENTUNO Q officially supports Ubuntu for predictable long-term support and extensive package ecosystems, and Debian with full upstream support for embedded-focused development.
The M.2 connector supports NVMe SSDs.
VENTUNO Q supports multiple AI deployment paths: Qualcomm® AI Hub pre-optimized models, Edge Impulse trained models, Arduino App Lab curated model library, 3rd party and custom inference engines.
Absolutely. Use Edge Impulse’s integrated platform to upload your training data; train models using Edge Impulse’s cloud infrastructure; automatically optimize and quantize for VENTUNO Q hardware; deploy directly into Arduino App Lab with one click. You can also train your own models on 3rd-party and custom inference engines.
Yes, VENTUNO Q is compatible with ROS 2.
VENTUNO Q is coming soon! To ensure you’re among the first to get your hands on it, sign up for our availability alerts. We’ll notify you the moment it hits the shelves at the Arduino Store and our official resellers, such as Digikey, Farnell, Macfos, Mouser and RS. Stay tuned!
Qualcomm branded products are products of Qualcomm Technologies, Inc. and/or its subsidiaries. Arduino, VENTUNO, UNO, and Modulino are trademarks or registered trademarks of Arduino S.r.l.