VENTUNO Q is the definitive powerhouse for AI and robotics applications.
The edge AI computer that redefines what's possible.
The Dragonwing IQ-8275 processor delivers NPU, CPU, and GPU for complex neural network inference – with an outstanding 40 dense TOPS.
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.
Use Qwen 4 or Gemma 4 for sophisticated natural language understanding entirely on-device, without cloud dependencies or data transmission.
Models like Qwen 3 VLM combines visual perception with natural language understanding for image captioning, scene description, OCR, and more.
Leverage Melo TTS and Whisper to 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 models like PoseNet. For fitness applications, safety monitoring, and interactive gaming.
Open a curated example and watch AI run in real time, no code required.
Modify a ready-to-use example: adjust parameters, tweak the code, instantly update your app.
Bring your own model from Hugging Face or Qualcomm AI Hub, or train one with Edge Impulse.
Customize using your own toolchains, and build advanced pipelines with the full power of Linux.
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.
AI-capable assistants that operate entirely offline, ensuring complete data privacy. Perfect for smart kiosks, healthcare assistants, traffic flow analysis, and more.
The complete robotics stack: vision processing for environmental awareness combined with deterministic motor control for precise manipulation and navigation.
Automated quality control, predictive maintenance, and process optimization: all while meeting industrial reliability, safety, and connectivity standards.
A powerful, flexible platform for prototyping algorithms, publishing breakthrough research, and teaching advanced AI and robotics concepts.
High-bandwidth 16 GB RAM enables concurrent multi-model AI inference.
Industrial-grade eMMC, plus M.2 connector for NVMe Gen.4 storage expansion.
Three 4-lane interfaces for 360° awareness, stereo depth perception, and multi-angle inspection.
MIPI-DSI for touchscreens and interactive panels, HDMI for monitors and projectors, USB-C DisplayPort Alt Mode for versatile video output.
Tri-band Wi-Fi®️ 6 (2.4/5/6 GHz) and Bluetooth®️ 5.3 for wireless connectivity. 2.5 Gb Ethernet.
USB-C for high-speed vision and audio data transfer. Dual USB-A 3.0 ports for peripherals and storage.
CAN-FD for professional motor controllers and industrial networks. PWM and deterministic GPIO for sub-millisecond response.
Native compatibility with all UNO shields, motor controllers, sensors, and wireless interfaces work out of the box.
Standard 40-pin GPIO header provides full electrical and mechanical compatibility with Raspberry Pi accessories.
Solder-free Qwiic connector supports chainable Modulino nodes and hundreds of Qwiic-compatible sensors with polarized, error-proof connections.
Advanced carrier headers (JMEDIA, JOMEGA, JMISC) provide dedicated lanes for high-speed cameras, displays, multi-axis control, and sensor fusion.
Works with Arduino™ certifies third-party System-on-Modules as fully compatible with the Arduino ecosystem. Any app you build in Arduino App Lab on UNO Q or VENTUNO Q runs on a certified SOM with zero code changes. A guaranteed production path for developers, and a credible badge for SOM vendors.
| 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 |
Yes, VENTUNO Q is a real, standard Ubuntu computer. This means 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! Arduino App Lab is the fast path, not a requirement.
VENTUNO Q delivers up to 40 dense TOPS of AI compute, supporting Qwen 3 4B LLM; Qwen 2.5 7B and 3 4B VLM; Gemma 4 E2B and E4B; Whisper ASR; Melo and Piper TTS; YoloX small object detection; MediaPipe gesture recognition; and more.
Get started with ready-to-run Bricks, optimized for the onboard NPU through Qualcomm® AI Hub. For generative AI use cases, VENTUNO Q supports LLM inference via llama.cpp and GGUF models, ideal for running locally at the edge. You can also run these models with GenieX, the open-source Gen AI runtime by Qualcomm. At the same time, you can work with familiar frameworks like PyTorch and other advanced AI stacks, enabling custom model development, optimization, and deployment tailored to specific applications.
VENTUNO Q is designed to take you from idea to deployed application – not just working prototype. At the heart of this experience is Arduino App Lab, a complete end-to-end platform for building, deploying, and managing AI applications that goes well beyond what any other edge AI board offers today, making professional-grade edge AI accessible at every skill level.
A dual-brain architecture of VENTUNO Q combines up to 40 dense TOPS of AI compute with a dedicated real-time microcontroller, enabling both intelligent inference and deterministic actuation in a single board. This is ideal for robotics, industrial control, and any application where AI must interact with the physical world. Broad ecosystem compatibility with UNO shields, Raspberry Pi Hats, and Modulino nodes keeps prototyping fast and familiar.
VENTUNO Q ships with pre-loaded Ubuntu, distributed by Canonical, and bundled with Ubuntu Pro license that delivers enterprise-grade security updates - which make it immediately viable for professional, commercial, and industrial developers. It supports Debian (coming soon) with full upstream. It supports for embedded-focused development. The microcontroller side of its dual architecture runs the Arduino Core on Zephyr RTOS.
VENTUNO Q comes with 16 (2 X 8) GB of LPDDR5 RAM and 64 GB of eMMC onboard storage, working together so you can run real AI on the board — on the edge and offline.
16 GB RAM is your fast working memory — enough to load generative models (LLMs and VLMs like Qwen 3 and Gemma 4, plus larger GGUF models), run inference, and keep your app and Ubuntu going all at once. That's roughly double the memory of typical 8 GB edge boards, so you can work with bigger models and richer multimodal pipelines without hitting a ceiling.
64 GB onboard storage is where Ubuntu, your AI models, your application, and your data live. Because VENTUNO Q boots and runs from fast, soldered-down storage rather than a removable microSD card, you get reliable, repeatable boots and performance built to ship and stay in the field.
The M.2 connector supports NVMe SSDs.
Absolutely. You can train your own models on 3rd-party and custom inference engines. We recommend using Edge Impulse’s integrated platform to upload your training data, train models on the cloud infrastructure, and automatically optimize and quantize for VENTUNO Q hardware – then you can deploy directly into Arduino App Lab with one click!
Yes, VENTUNO Q is compatible with ROS 2.
Yes. Through the Works with Arduino™ Program, VENTUNO Q gives you a clear path from prototyping to production. Develop and validate on VENTUNO Q, then move to a third-party SOM built on the same Qualcomm Dragonwing™ IQ8 — scaling your product while preserving your software investment, since compatible Arduino Apps port across with zero code changes. Certified partners include SECO, with its SOM-SMARC-Dragonwing-IQ8 and Clea software platform, and Toradex, with its Aquila IQ8 and Torizon platform. And more OEMs are collaborating with Arduino and Qualcomm to bring additional Works with Arduino certified products to market.
Learn more about the Works with Arduino Certification Program.
The future of edge AI and robotics isn’t just intelligent, it’s actionable. VENTUNO Q delivers the compute power, real-time control, and development ecosystem you need to transform your ideas into production-ready systems.
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.