Sipeed MAIX-I module WiFi version - eucaiot Store
Sipeed MAIX-I module WiFi version - eucaiot Store
Sipeed MAIX-I module WiFi version - eucaiot Store

Seeed Studio

Sipeed MAIX-I module WiFi version

Sale priceR 199.43
SKU: 114991684



Sipeed MAix: AI at the edge

AI is pervasive today, from consumer to enterprise applications. With the explosive growth of connected devices, combined with a demand for privacy/confidentiality, low latency, and bandwidth constraints, AI models trained in the cloud increasingly need to be run at the edge.

MAIX is Sipeed’s purpose-built module designed to run AI at the edge, we called it AIoT. It delivers high performance in a small physical and power footprint, enabling the deployment of high-accuracy AI at the edge, and the competitive price makes it possible to embed to any IoT device. As you see, Sipeed MAIX is quite like Google edge TPU, but it acts as a master controller, not an accelerator like edge TPU, so it is more low cost and low power than the AP+edge TPU solution.

MAix's Advantage and Usage Scenarios:

  • MAIX is not only hardware but also provides an end-to-end, hardware + software infrastructure for facilitating the deployment of customers' AI-based solutions.
  • Thanks to its performance, small footprint, low power, and low cost, MAIX enables the broad deployment of high-quality AI at the edge.
  • MAIX isn't just a hardware solution, it combines custom hardware, open software, and state-of-the-art AI algorithms to provide high-quality, easy-to-deploy AI solutions for the edge.
  • MAIX can be used for a growing number of industrial use cases such as predictive maintenance, anomaly detection, machine vision, robotics, voice recognition, and many more. It can be used in manufacturing, on-premise, healthcare, retail, smart spaces, transportation, etc.

MAix's CPU

  • In hardware, MAIX has a powerful KPU K210 inside, it offers many exciting features:
  • 1st competitive RISC-V chip, also 1st competitive AI chip, newly released in Sep. 2018
  • 28nm process, dual-core RISC-V 64bit IMAFDC, on-chip huge 8MB high-speed SRAM (not for XMR :D), 400MHz frequency (able to 800MHz)
  • KPU (Neural Network Processor) inside, 64 KPU which is 576bit width, supports convolution kernels, any form of the activation function. It offers 0.25TOPS@0.3W,400MHz, when overclocking to 800MHz, it offers 0.5TOPS. It means you can do object recognition 60fps@VGA
  • APU (Audio Processor) inside, support 8mics, up to 192KHz sample rate, hardcore FFT unit inside, easy to make a Mic Array (MAIX offers it too)
  • Flexible FPIOA (Field Programmable IO Array), you can map 255 functions to all 48 GPIOs on the chip
  • DVP camera and MCU LCD interface, you can connect a DVP camera, run your algorithm, and display on LCD
  • Many other accelerators and peripherals: AES Accelerator, SHA256 Accelerator, FFT Accelerator (not APU's one), OTP, UART, WDT, IIC, SPI, I2S, TIMER, RTC, PWM, etc.

MAix's Module

Inherit the advantage of K210's small footprint, Sipeed MAIX-I module, or called M1, integrate K210, 3-channel DC-DC power, 16MB Flash (M1w module add wifi chip esp8285 on it) into Square Inch Module. All usable IO breaks out as 1.27mm(50mil) pins, and the pin's voltage is selectable from 3.3V and 1.8V.

Sipeed Maix  block pin

MAIX's development board (M1 dock & M1w dock, w means WiFi version)

Firstly, We make a prototype development board for M1, called M1 dock or Dan Dock, it is simple, small, and cheap, but all functions include.

As many DIYers want to build their own work with a breadboard, Sipeed newly provide breadboard-friendly board for you, it is called MAix BiT

  • It is twice M1 size, 1x2 inch size, breadboard-friendly, and also SMT-able,
  • It integrates a USB2UART chip, auto download circuit, RGB LED, DVP Camera FPC connector(support small FPC camera and standard M12 camera), MCU LCD FPC connector(support our 2.4-inch QVGA LCD), and TF card slot.
  • MAix BiT is able to adjust core voltage! you can adjust from 0.8V~1.2V, overclock to 800MHz!
2 bit


And the bigger and better MAIX's development board Sipeed MAIX Go

MAix Go is bigger and better than M1 Dock.

  • It is 88x60mm, all pins out, with a standard M12 lens DVP camera, and the Camera can be flipped from front to rear!
  • It has onboard JTAG&UART based on STM32F103C8, so you can debug M1 without extra Jlink.
  • It has a lithium battery manager chip with a power path management function, you can use the board with lithium battery and USB power without conflict~
  • It has I2S Mic, Speaker, RGB LED, Mic array connector, thumbwheel, TF card Slot, and so on.
  • This suit includes a 2.8-inch LCD too and has a simple case for it.
2 Sipeed Go

MAIX's peripheral module

We have seen basic camera and LCD interface on board, so DVP Camera and MCU LCD is supported very early.

It supports OV7725, OV2640(default, 2M), and OV5640 for the moment. And it supports 2.4 inch st7789, and 2.8 inches ili9341 LCD in QVGA resolution.

We have an extra tiny I2S mic module and a Cool  6+1 Microphone Array Module


Sipeed 6+1 Microphone Arra is a 6-microphone expansion board for Maix AI development boards designed for AI and voice applications.

Including 6+1 digital microphones and 12 three-color LEDs, it supports sound localization, beam forming, speech recognition, etc.


Next, we have a Binocular camera module! You can try binocular stereo vision with it

Sipeed Binocular camera module is a camera expansion board for Maix AI development boards designed for AI and Binocular stereo vision applications.
It supports Binocular stereo vision and depth vision. The camera(OV2640 or OV7725) and I2S mic are optional. sipeed binocular camera

MAix's SoftWare

MAIX supports the original standalone SDK, FreeRTOS SDK based on C/C++.
And we port micropython on it: It supports FPIOA, GPIO, TIMER, PWM, Flash, OV2640, LCD, etc. And it has zmodem, vi, and SPIFFS on it, you can edit python directly or sz/rz file to board. We are glad to see you contribute to it: //Maixpy project //Maixpy wiki project

MAix's Deep learning

MAIX supports a fixed-point model that the mainstream training framework trains, according to specific restriction rules, and have a model compiler to compile models to its own model format.
It supports tiny-Yolo, mobile net-v1, and, TensorFlow Lite! Many TensorFlow Lite models can be compiled and run on MAIX! And We will soon release a model shop, you can trade your model on it.


CPU : RISC-V Dual Core 64bit, 400Mh adjustable Powerful dual-core 64-bit open architecture-based
processor with rich community resources
FPU Specifications IEEE754-2008 compliant high-performance pipelined FPU
Debugging Support High-speed UART and JTAG interface for debugging
Neural Network Processor (KPU) • Supports the fixed-point model that the mainstream training framework trains according to specific restriction rules
• There is no direct limit on the number of network layers, and each layer of convolutional neural network parameters can be configured separately, including the number of input and output channels, and the input and output line width and column height
• Support for 1x1 and 3x3 convolution kernels
• Support for any form of activation function
• The maximum supported neural network parameter size for real-time work is 5MiB to 5.9MiB
• The maximum supported network parameter size when
working in non-real time is (flash size - software size)
Audio Processor (APU) • Up to 8 channels of audio input data, ie 4 stereo channels
•  Simultaneous scanning pre-processing and beamforming for sound sources in up to 16 directions
• Supports one active voice stream output
• 16-bit wide internal audio signal processing
• Support for 12-bit, 16-bit, 24-bit, and 32-bit input data widths • Multi-channel direct raw signal output
• Up to 192kHz sample rate
• Built-in FFT unit supports 512-point FFT of audio data
•Uses system DMAC to store output data in system memory
Static Random-Access Memory (SRAM) The SRAM is split into two parts, 6MiB of on-chip
general-purpose SRAM memory and 2MiB of on-chip AI SRAM memory, for a total of 8MiB
Field Programmable IO Array (FPIOA/IOMUX) FPIOA allows users to map 255 internal functions to 48
free IOs on the chip
Digital Video Port (DVP) Maximum frame size 640x480
FFT Accelerator The FFT accelerator is a hardware implementation of the
Fast Fourier Transform (FFT)
FreeRtos & Standard SDK Support FreeRtos and Standard development kit.
MicroPython Support Support MicroPython on M1
Machine vision Machine vision based on convolutional neural network
Machine hearing A high-performance microphone array processor
Supply voltage of external power supply 4.8V ~ 5.2V
Supply current of external power supply >600mA
Temperature rise <30K
Range of working temperature -30℃ ~ 85℃
MCU : ESP8285 Tensilica L106 32-bit MCU
Wireless Standard 802.11 b/g/n
Frequency Range 2400Mhz - 2483.5Mhz
TX Power(Conduction test) 802.11.b : +15dBm
802.11.g : +10dBm(54Mbps)
802.11.n : +10dBm (65Mbps)
Antenna Connector IPEX 3.0x3.0mm
Wi-Fi mode Station/SoftAP/SoftAP+Station

Technical details

Dimensions 25mm x25mm x1mm
Weight G.W 8g
Battery Exclude

Part List

Sipeed MAIX-I module WiFi version 1
HSCODE 9031900090