{"product_id":"arduino-ventuno-q","title":"Arduino Ventuno Q","description":"\u003cp\u003e\u003cstrong\u003eArduino Ventuno Q is a dual-brain edge AI and robotics platform delivering up to 40 dense TOPS of AI acceleration alongside fast, precise control of connected hardware.\u003c\/strong\u003e\u003c\/p\u003e\n\u003chr\u003e\n\u003cp\u003eBuilt around a \u003cstrong\u003edual-brain architecture\u003c\/strong\u003e that pairs a \u003ca href=\"https:\/\/www.qualcomm.com\/internet-of-things\/products\/iq8-series\" rel=\"noopener\" title=\"Qualcomm Dragonwing™ IQ8\" target=\"_blank\"\u003eQualcomm Dragonwing™ IQ8\u003c\/a\u003e MPU with a dedicated \u003ca href=\"https:\/\/www.st.com\/en\/microcontrollers-microprocessors\/stm32h5-series.html\" rel=\"noopener\" title=\"STM32H5\" target=\"_blank\"\u003eSTM32H5\u003c\/a\u003e real-time microcontroller, \u003ca href=\"\/collections\/arduino-store\" title=\"Arduino\"\u003eArduino\u003c\/a\u003e \u003cstrong\u003eVentuno Q\u003c\/strong\u003e doesn’t just interpret the world, it interacts with it. So you get sensing, decision, and action all on one board, on the edge, offline.\u003c\/p\u003e\n\u003cp\u003eThe AI brain delivers up to \u003cstrong\u003e40 dense TOPS of NPU\u003c\/strong\u003e acceleration for vision models, LLMs, and multi-modal AI inference. The action brain runs the Arduino Core on \u003cstrong\u003eZephyr RTOS\u003c\/strong\u003e, enabling \u003cstrong\u003esub-millisecond, deterministic control of motors, CAN-FD, PWM, and GPIO\u003c\/strong\u003e. The two communicate seamlessly via an RPC bridge: no multi-device complexity, no latency penalty, no compromise.\u003c\/p\u003e\n\u003cp\u003eIt’s the most powerful Arduino platform to date, offering \u003cstrong\u003e16 GB LPDDR5 RAM\u003c\/strong\u003e and \u003cstrong\u003e64 GB industrial-grade eMMC\u003c\/strong\u003e. On the MPU side, it runs standard upstream \u003cstrong\u003eUbuntu\u003c\/strong\u003e \u003cstrong\u003e(and Debian coming soon) Linux\u003c\/strong\u003e. Yet it maintains the openness, versatility, and ease of use that Arduino has become synonymous for.\u003c\/p\u003e\n\u003cp\u003e\u003ca href=\"https:\/\/www.docker.com\/\" rel=\"noopener\" title=\"Docker\" target=\"_blank\"\u003eDocker\u003c\/a\u003e and apt are already installed and available on the board, and it’s \u003cstrong\u003ecompatible with VS Code, PyCharm, and Jupyter\u003c\/strong\u003e - with no proprietary SDK and no lock-in.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003ePower supply not included.\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003ciframe width=\"560\" height=\"315\" src=\"https:\/\/www.youtube.com\/embed\/jOs37MSag6A?si=WiSK2h9ULeKuOsfm\" title=\"YouTube video player\"\u003e\u003c\/iframe\u003e\u003c\/p\u003e\n\u003ch3\u003eOne board - three ways to build with AI\u003c\/h3\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eReady to run.\u003c\/strong\u003e A curated library of NPU-optimized models is available out of the box via Arduino® App Lab and Qualcomm® AI Hub - no configuration required. Run Qwen and Gemma 4 LLMs and VLMs, Whisper ASR, Melo TTS and Piper, MediaPipe gesture recognition, YOLO-X object tracking, and keyword spotting. More models added continuously.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eBring your own model (BYOM).\u003c\/strong\u003e Upload any GGUF-format model from Hugging Face or Qualcomm AI Hub directly via the llama.cpp brick in Arduino App Lab and build on it immediately – compatible with the full open-weight ecosystem, no framework migration required.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003eTrain your own model (TYOM).\u003c\/strong\u003e Use the integrated Edge Impulse Studio to train and quantize custom models, optimized for the Dragonwing IQ8 NPU and deployed directly into Arduino App Lab with one click.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch3\u003eArduino App Lab: a unified experience (but not your only option!)\u003c\/h3\u003e\n\u003cp\u003eYou can program Ventuno Q with the tools you are used to. Or you can enjoy the all-new \u003ca href=\"https:\/\/docs.arduino.cc\/software\/app-lab\/\" rel=\"noopener\" title=\"Arduino App Lab\" target=\"_blank\"\u003eArduino App Lab\u003c\/a\u003e, for an integrated development environment that unifies the journey across Linux and real-time OS.\u003c\/p\u003e\n\u003cp\u003ePreloaded on Ventuno Q, Arduino App Lab combines Arduino Sketches, Python scripts, and containerized AI models into fully integrated applications, all managed from a single interface.\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cstrong\u003eReady-to-use Apps and Bricks.\u003c\/strong\u003e Get started fast with Arduino Apps, self-contained examples with everything you need. Add plug-and-play features to your projects with pre-built Bricks to accelerate your ideas even more.\u003c\/li\u003e\n\u003cli\u003e\n\u003cstrong\u003ePre-loaded AI Models.\u003c\/strong\u003e With pre-loaded AI models in Arduino App Lab, you can leverage real-world data for a wide range of capabilities such as object\/human detection, anomaly detection, image classification, sound recognition, and keyword spotting.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch2\u003eFeatures\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003eQualcomm Dragonwing™ IQ8 (QCS8275) MPU with octa-core Arm® Cortex® CPU\u003c\/li\u003e\n\u003cli\u003eST STM32H5F5 Arm® Cortex®-M33 real-time MCU up to 250 MHz, with 4 MB Flash and 1.5 MB RAM\u003c\/li\u003e\n\u003cli\u003eHexagon™ Tensor AI Processor up to 40 dense TOPS, Adreno™ 623 GPU, Adreno™ VPU 623 and Qualcomm Spectra 692 ISP\u003c\/li\u003e\n\u003cli\u003e16 GB LPDDR5 RAM and 64 GB eMMC storage\u003c\/li\u003e\n\u003cli\u003eM.2 Key M 2230 connector for non-bootable NVMe Gen 4 storage via PCIe x4\u003c\/li\u003e\n\u003cli\u003eUbuntu Linux OS with Debian support, plus Arduino Core on Zephyr OS for the MCU\u003c\/li\u003e\n\u003cli\u003eArduino Bridge RPC communication between the MPU and MCU\u003c\/li\u003e\n\u003cli\u003eTensorFlow Lite, ONNX Runtime and PyTorch support, with Qualcomm AI Stack, Arduino App Lab and Edge Impulse Studio integration\u003c\/li\u003e\n\u003cli\u003eTri-band Wi-Fi® 6 (2.4\/5\/6 GHz), Bluetooth® 5.3 and 2.5 Gbit RJ45 Ethernet\u003c\/li\u003e\n\u003cli\u003eUSB connectivity\n\u003cul\u003e\n\u003cli\u003e1× USB-C with host\/device and power role switching, DisplayPort Alt Mode and USB Power Delivery up to 20 V\u003c\/li\u003e\n\u003cli\u003e2× USB 3.0 Type-A ports\u003c\/li\u003e\n\u003cli\u003e2× USB 3.0 interfaces via JOMEGA\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/li\u003e\n\u003cli\u003eHDMI, USB-C DisplayPort Alt Mode and MIPI DSI display outputs\u003c\/li\u003e\n\u003cli\u003e3× onboard 4-lane MIPI CSI-2 camera connectors, plus MIPI CSI0\/CSI1 via JMEDIA\u003c\/li\u003e\n\u003cli\u003eMAX98091ETM+T audio codec with mono line out, mono speaker out, stereo headphone out and microphone input\u003c\/li\u003e\n\u003cli\u003eCAN-FD connectivity\n\u003cul\u003e\n\u003cli\u003e1× CAN-FD with ATA6563-GBQW1 PHY and onboard split termination via screw terminal\u003c\/li\u003e\n\u003cli\u003e3× CAN-FD without PHY via JOMEGA\u003c\/li\u003e\n\u003cli\u003e1× CAN-FD without PHY via UNO Shield headers\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/li\u003e\n\u003cli\u003eArduino UNO Shield-compatible headers, Raspberry Pi® HAT-compatible 40-pin JHAT and 3.3 V Qwiic connector\u003c\/li\u003e\n\u003cli\u003ePower via USB-C PD 9-20 V up to 3 A, 7-24 V 5.5×2.1 mm barrel jack up to 5 A or 7-24 V screw terminal up to 10 A\u003c\/li\u003e\n\u003cli\u003e160 mm × 100 mm board, 25.8 mm high without the SoM heatsink and fan\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch2\u003eSpecifications\u003c\/h2\u003e\n\u003ctable\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cstrong\u003eMicroprocessor (MPU)\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003eQualcomm Dragonwing™ IQ8 (QCS8275):\u003cbr\u003eOcta-core Qualcomm®Kryo™Gen 6 CPU\u003cbr\u003eQualcomm® Adreno™ 623 GPU\u003cbr\u003eQualcomm® Hexagon™ Tensor AI Processor (NPU): up to 40 Dense TOPS\u003cbr\u003eQualcomm Spectra™ 690 ISP\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cstrong\u003eMicrocontroller (MCU)\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003eSTM32H5F5:\u003cbr\u003eArm® Cortex® M33 at 250MHz\u003cbr\u003e4MB flash\u003cbr\u003e1.5MB RAM\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cstrong\u003eRAM\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e2x8GB LPDDR5\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cstrong\u003eStorage\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e64GB eMMC\u003cbr\u003eM.2 connector for NVME Gen.4 external storage\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cstrong\u003eConnectivity\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003eWi-Fi® 6 2.4\/5\/6 GHz with onboard antenna\u003cbr\u003eBluetooth® 5.3 with onboard antenna\u003cbr\u003e1x 2.5Gbit RJ45 Ethernet\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cstrong\u003eUSB\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e1× USB-C port with host\/device role switching, power role switch and video output\u003cbr\u003e2x USB 3.0 Type A\u003cbr\u003e2x USB 3.0 on JOMEGA header\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cstrong\u003eCamera\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003eUSB camera support\u003cbr\u003e3x MIPI CSI connectors muxed with 2x MIPI CSI on JMEDIA header\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cstrong\u003eVideo\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e1x HDMI muxed with MIPI DSI on JMEDIA header\u003cbr\u003eVideo output (DP Alt mode) support via USB-C\u003cbr\u003eMIPI DSI pins on JMEDIA header\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cstrong\u003eAudio\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e2x Microphone IN \/ Headphone OUT \/ Ear OUT \/ Line OUT on JMISC header\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cstrong\u003eCAN\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e1x CAN-FD PHY on screw terminal\u003cbr\u003e3x CAN-FD (no PHY) on JOMEGA header\u003cbr\u003e1x CAN-FD (no PHY) on UNO Shield headers\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cstrong\u003eInterfaces\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003eI2C\/I3C\u003cbr\u003eSPI\u003cbr\u003ePWM\u003cbr\u003eUART\u003cbr\u003e4× RGB user-controllable LEDs\u003cbr\u003e8x13 Blue LED Matrix\u003cbr\u003e1x Qwiic connector voltage 3V3, I2C\u003cbr\u003e1x User push-button\u003cbr\u003e1x reset button\u003cbr\u003eJCTL: MPU Remote Debug connector\u003cbr\u003eJTAG port on JOMEGA\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\n\u003cstrong\u003ePower\u003c\/strong\u003e \u003cstrong\u003eSupply\u003c\/strong\u003e\n\u003c\/td\u003e\n\u003ctd\u003eFrom USB-C connector 5 VDC max 5.5x2.1 mm Power Jack 12-24 VDC\u003cbr\u003eScrew Terminal 7-24 VDC\u003cbr\u003e7-24 V on JOMEGA\u003cbr\u003e\u003cbr\u003eNote: Use a PD-capable power supply of at least 50 W to start, or up to 65 W for full AI workloads and peripherals, through USB-C PD, barrel jack, or screw terminal within stated limits.\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cstrong\u003eTemperature Range\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003eCommercial Temperature Range: -10 °C to +60 °C (14 °F to 140 °F)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003e\u003cstrong\u003eDimensions\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e160x100x25.8 mm\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003ch2\u003eResources\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003e\u003ca href=\"https:\/\/docs.arduino.cc\/hardware\/ventuno-q\" title=\"Ventuno Q documentation\"\u003eDocumentation\u003c\/a\u003e\u003c\/li\u003e\n\u003cli\u003e\u003ca href=\"https:\/\/docs.arduino.cc\/resources\/datasheets\/ABX00181-datasheet.pdf\" title=\"Datasheet\" rel=\"noopener\" target=\"_blank\"\u003eDatasheet\u003c\/a\u003e\u003c\/li\u003e\n\u003cli\u003e\u003ca href=\"https:\/\/docs.arduino.cc\/software\/app-lab\/\" title=\"Arduino App Llab\" rel=\"noopener\" target=\"_blank\"\u003eArduino App Lab\u003c\/a\u003e\u003c\/li\u003e\n\u003cli\u003e\u003ca href=\"https:\/\/forum.arduino.cc\/c\/official-hardware\/ventuno-q\/227\" title=\"Arduino forum\" rel=\"noopener\" target=\"_blank\"\u003eArduino forum\u003c\/a\u003e\u003c\/li\u003e\n\u003cli\u003eProduct number: Arduino ABX00181\u003c\/li\u003e\n\u003cli\u003eEAN: 7630049205949\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003ch2\u003ePackage Contents\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003e1x Arduino Ventuno Q\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e\u003cstrong\u003ePower supply not included.\u003c\/strong\u003e\u003c\/p\u003e","brand":"Arduino","offers":[{"title":"Default Title","offer_id":56175581430145,"sku":"ABX00181","price":251.9,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0176\/3274\/files\/arduino-ventuno-q-arduino-abx00181-1255774527.jpg?v=1787676432","url":"https:\/\/thepihut.com\/products\/arduino-ventuno-q","provider":"The Pi Hut","version":"1.0","type":"link"}