{"product_id":"sipeed-maix-i-module-w-o-wifi-1st-risc-v-64-ai-module-k210-inside","title":"Sipeed MAIX-I module w\/o WiFi ( 1st RISC-V 64 AI Module, K210 inside )","description":"\u003cmeta name=\"description\" content=\"Buy Sipeed MAIX-I module w\/o WiFi ( 1st RISC-V 64 AI Module, K210 inside ) online in India at best price from The Tech Depot, Bengaluru. Authentic product, 7-day warranty on manufacturing defects, fast delivery across India.\"\u003e\n\n\u003ch1\u003eSipeed MAIX-I module w\/o WiFi ( 1st RISC-V 64 AI Module, K210 inside )\u003c\/h1\u003e\n\n\u003cp\u003eThe Sipeed MAIX-I is the first commercial RISC-V 64-bit AI accelerator module powered by the Kendryte K210 dual-core processor, designed for edge AI inference and machine learning applications without WiFi connectivity. This module is extensively used by embedded systems engineers, robotics developers, and IoT specialists who require low-power AI processing at the edge without network dependencies. It solves the critical challenge of deploying neural networks and computer vision algorithms on resource-constrained devices while maintaining ultra-low power consumption and deterministic latency.\u003c\/p\u003e\n\n\u003ch2\u003eProduct Overview\u003c\/h2\u003e\n\u003cp\u003eThe Sipeed MAIX-I module integrates the K210 System-on-Chip featuring dual-core RISC-V processors running at 400MHz, with an integrated neural network accelerator (KPU) capable of processing convolutional neural networks with 8-bit quantized models. The architecture includes 8MB of SRAM for fast computation, hardware support for common activation functions, and dedicated image processing units for real-time computer vision tasks. The module operates at exceptionally low power consumption (typically under 1W during inference), making it ideal for battery-powered and embedded applications where traditional GPU-based solutions are impractical.\u003c\/p\u003e\n\n\u003cp\u003eWhat distinguishes the MAIX-I is its purpose-built neural processing architecture optimized for inference rather than training, combined with the RISC-V instruction set that provides open-source software ecosystem advantages. The absence of WiFi in this variant reduces power consumption and cost while maintaining full AI processing capabilities, making it perfect for standalone edge devices, autonomous robots, industrial vision systems, and smart sensors. The module supports popular frameworks like TensorFlow Lite and ONNX through conversion tools, enabling developers to deploy pre-trained models with minimal optimization effort.\u003c\/p\u003e\n\n\u003ch2\u003eKey Specifications\u003c\/h2\u003e\n\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd\u003eSpecification\u003c\/td\u003e\n\u003ctd\u003eDetails\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eProduct Type\u003c\/td\u003e\n\u003ctd\u003eRISC-V 64-bit AI Accelerator Module\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eBrand\u003c\/td\u003e\n\u003ctd\u003eSipeed\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eProcessor\u003c\/td\u003e\n\u003ctd\u003eKendryte K210 Dual-Core RISC-V 64-bit at 400MHz\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eNeural Network Accelerator\u003c\/td\u003e\n\u003ctd\u003eKPU with 8-bit quantization support\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eMemory\u003c\/td\u003e\n\u003ctd\u003e8MB SRAM, supports external SPI Flash\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePower Consumption\u003c\/td\u003e\n\u003ctd\u003eTypically under 1W during inference\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eConnectivity\u003c\/td\u003e\n\u003ctd\u003eNo WiFi (WiFi-less variant)\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eInterfaces\u003c\/td\u003e\n\u003ctd\u003eSPI, I2C, UART, GPIO\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eOperating Voltage\u003c\/td\u003e\n\u003ctd\u003e1.8V to 3.3V\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eOrigin\u003c\/td\u003e\n\u003ctd\u003eOriginal\/Authentic\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eWarranty\u003c\/td\u003e\n\u003ctd\u003e7 days on manufacturing defects\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eShipping\u003c\/td\u003e\n\u003ctd\u003e1-5 days from Bengaluru\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eDelivery\u003c\/td\u003e\n\u003ctd\u003e7-8 days across India\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eSupport\u003c\/td\u003e\n\u003ctd\u003e24\/7 via Email and WhatsApp\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/table\u003e\n\n\u003ch2\u003eKey Features\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003eDual-Core RISC-V 64-bit Processor at 400MHz with dedicated KPU neural network accelerator for real-time AI inference without external GPU dependency\u003c\/li\u003e\n\u003cli\u003e8MB embedded SRAM enabling fast model execution with support for 8-bit quantized neural networks and common activation functions\u003c\/li\u003e\n\u003cli\u003eUltra-low power consumption under 1W during inference, ideal for battery-powered IoT devices, drones, and mobile robotics applications\u003c\/li\u003e\n\u003cli\u003eOpen RISC-V instruction set architecture with comprehensive software ecosystem including MicroPython, Rust, and C\/C++ support\u003c\/li\u003e\n\u003cli\u003eIntegrated image processing unit supporting camera input for real-time computer vision tasks including object detection and face recognition\u003c\/li\u003e\n\u003cli\u003eMultiple communication interfaces including SPI, I2C, UART, and GPIO for seamless integration with sensors and peripherals\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch2\u003eApplications and Use Cases\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003eEdge AI Computer Vision: Deploy real-time object detection, face recognition, and pose estimation on autonomous robots and surveillance systems without cloud connectivity\u003c\/li\u003e\n\u003cli\u003eIndustrial IoT and Smart Sensors: Implement predictive maintenance models and anomaly detection on factory equipment with deterministic latency and offline processing capability\u003c\/li\u003e\n\u003cli\u003eAutonomous Robotics: Power self-driving robots, drones, and autonomous vehicles with onboard AI inference for navigation, obstacle avoidance, and decision-making\u003c\/li\u003e\n\u003cli\u003eSmart Home and Consumer Electronics: Enable intelligent features in resource-constrained devices like smart doorbells, security cameras, and wearable devices with privacy-preserving local processing\u003c\/li\u003e\n\u003cli\u003eMedical and Healthcare Devices: Deploy diagnostic algorithms and vital sign monitoring on portable medical devices requiring real-time analysis without network latency\u003c\/li\u003e\n\u003cli\u003eAgricultural Technology: Implement crop disease detection, pest monitoring, and yield prediction models on field robots and drones for precision farming applications\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch2\u003eHow to Use\u003c\/h2\u003e\n\u003cp\u003eTo begin working with the Sipeed MAIX-I module, first establish the development environment by installing the Kendryte toolchain and MaixPy IDE on your computer. Connect the module to your development machine via USB, then use the IDE to write Python or C code for your AI application. The module supports importing pre-trained neural network models in ONNX or TensorFlow format, which can be quantized to 8-bit using provided conversion tools to fit within the 8MB SRAM constraint while maintaining acceptable accuracy.\u003c\/p\u003e\n\n\u003cp\u003eFor hardware integration, connect your camera module to the DVP camera interface, and configure other sensors through the available SPI, I2C, or UART interfaces using GPIO pins. The module operates at 1.8V to 3.3V, making it compatible with standard 3.3V logic circuits and microcontroller ecosystems. Program the inference pipeline to capture frames, preprocess images, run KPU inference, and output results through your chosen interface. The open-source MaixPy framework provides extensive examples for common tasks like object detection and face recognition, significantly accelerating development time for embedded AI projects.\u003c\/p\u003e\n\n\u003ch2\u003eFrequently Asked Questions\u003c\/h2\u003e\n\u003cdetails\u003e\n\u003csummary\u003eWhat is the difference between the MAIX-I with and without WiFi?\u003c\/summary\u003e\n\u003cp\u003eThe WiFi-less variant (this product) eliminates the WiFi module, reducing power consumption, cost, and PCB footprint while maintaining full AI processing capabilities. Choose this version if your application requires standalone edge inference without cloud connectivity. The WiFi variant is suitable for applications needing remote monitoring or firmware updates over the network.\u003c\/p\u003e\n\u003c\/details\u003e\n\u003cdetails\u003e\n\u003csummary\u003eCan I run TensorFlow or PyTorch models directly on the MAIX-I?\u003c\/summary\u003e\n\u003cp\u003eThe MAIX-I requires model conversion and quantization before deployment. TensorFlow Lite and ONNX models can be converted to the K210 format using provided tools. PyTorch models must first be converted to ONNX format, then to K210 format. The conversion process includes 8-bit quantization to fit within memory constraints. We recommend using pre-trained quantized models from the Sipeed model zoo for fastest deployment.\u003c\/p\u003e\n\u003c\/details\u003e\n\u003cdetails\u003e\n\u003csummary\u003eWhat is the maximum inference speed and accuracy for neural networks?\u003c\/summary\u003e\n\u003cp\u003eInference speed depends on model architecture and complexity, typically ranging from 10-100 FPS for common object detection models. The KPU supports 8-bit quantized models with minimal accuracy loss compared to full-precision versions. For a 224x224 MobileNet-style model, expect approximately 30-50 FPS. Larger models may require optimization or model pruning to achieve real-time performance within the 8MB SRAM limit.\u003c\/p\u003e\n\u003c\/details\u003e\n\u003cdetails\u003e\n\u003csummary\u003eIs external storage available for larger models?\u003c\/summary\u003e\n\u003cp\u003eYes, the K210 supports external SPI Flash for storing multiple models. While only 8MB SRAM is available for active inference, you can load different models from external storage as needed. This enables applications with multiple AI models that are loaded sequentially based on runtime requirements.\u003c\/p\u003e\n\u003c\/details\u003e\n\u003cdetails\u003e\n\u003csummary\u003eWhen will I receive my order?\u003c\/summary\u003e\n\u003cp\u003eOrders are dispatched within 1-5 business days from our Bengaluru warehouse. Delivery takes 7-8 days to most locations across India.\u003c\/p\u003e\n\u003c\/details\u003e\n\u003cdetails\u003e\n\u003csummary\u003eWhat is your return and warranty policy?\u003c\/summary\u003e\n\u003cp\u003eWe offer a 7-day return policy on manufacturing defects only. Contact support within 7 days of receipt for free replacement or full refund. Not applicable for user damage or misuse.\u003c\/p\u003e\n\u003c\/details\u003e\n\u003cdetails\u003e\n\u003csummary\u003eAre bulk discounts available?\u003c\/summary\u003e\n\u003cp\u003eYes, wholesale pricing for orders of 10 or more units. Contact our sales team via WhatsApp or email for a customized bulk quote.\u003c\/p\u003e\n\u003c\/details\u003e\n\n\u003ch2\u003eWhy Buy from The Tech Depot\u003c\/h2\u003e\n\u003cul\u003e\n\u003cli\u003eGenuine Products: Sourced directly from authorized distributors with authentication\u003c\/li\u003e\n\u003cli\u003eExpert Team: Our technical team validates every product before listing\u003c\/li\u003e\n\u003cli\u003eFast Shipping: Dispatched within 1-5 days from our Bengaluru warehouse\u003c\/li\u003e\n\u003cli\u003ePan-India Delivery: 7-8 days to Mumbai, Delhi, Chennai, Hyderabad, Pune, Kolkata\u003c\/li\u003e\n\u003cli\u003ePayment Options: COD, UPI, credit\/debit cards, net banking, EMI available\u003c\/li\u003e\n\u003cli\u003eTechnical Support: 24\/7 expert guidance via email and WhatsApp\u003c\/li\u003e\n\u003cli\u003eReturns: 7-day return policy on manufacturing defects only\u003c\/li\u003e\n\u003c\/ul\u003e\n\n\u003ch2\u003eBuy Sipeed MAIX-I module w\/o WiFi ( 1st RISC-V 64 AI Module, K210 inside ) Online in India\u003c\/h2\u003e\n\u003cp\u003ePurchase the \u003cstrong\u003eSipeed MAIX-I module w\/o WiFi ( 1st RISC-V 64 AI Module, K210 inside )\u003c\/strong\u003e online at \u003ca href=\"https:\/\/thetechdepot.in\"\u003eThe Tech Depot\u003c\/a\u003e, India's trusted source for genuine electronics. We deliver across Bengaluru, Mumbai, Delhi, Chennai, Hyderabad, Pune, Kolkata, Ahmedabad, Jaipur, and Surat. Get the best price on \u003cstrong\u003eSipeed MAIX-I module w\/o WiFi ( 1st RISC-V 64 AI Module, K210 inside )\u003c\/strong\u003e with fast shipping and expert support.\u003c\/p\u003e\n\u003cp\u003eOur team in Bengaluru is available 24\/7 to support your journey from product selection to project completion.\u003c\/p\u003e","brand":"The Tech Depot","offers":[{"title":"Default Title","offer_id":48744405958913,"sku":"TTD-11376","price":895.7,"currency_code":"INR","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0819\/1577\/3185\/files\/062a84b88b16660d56037e00d474b1ac.jpg?v=1778073663","url":"https:\/\/techdepot.in\/products\/sipeed-maix-i-module-w-o-wifi-1st-risc-v-64-ai-module-k210-inside","provider":"Tech Depot India","version":"1.0","type":"link"}