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Espressif introduces new 2.4GHz Wi-Fi and Bluetooth LE 5.0 solution ESP32-S3


Bluetooth LE5.0 solution ESP32-S3

ESP32-S3 Applications & Features

ESP32-S3  is a dual-core XTensa LX7 MCU, capable of running at 240 MHz. Apart from its 512 KB of internal SRAM, it also comes with integrated 2.4 GHz, 802.11 b/g/n Wi-Fi and Bluetooth-Low-Energy 5.0 connectivity that provides long-range support. It has 44 programmable GPIOs and supports a rich set of peripherals. ESP32-S3 supports larger, high-speed octal SPI flash, and PSRAM with configurable data and instruction cache.

The IoT field is rapidly evolving and many applications need now a high level of machine learning and neural network capabilities. Edge devices are required to perform complex vector operations in order to implement demanding tasks like image and audio recognition, speech synthesis, regressions or classifications. Because of the massive data quantity processed, security is now a main concern and must be supported at device level by hardware peripherals.

The ESP32-S3 is the first certified Bluetooth 5 and wifi small combo module targeted at AIoT (artificial intelligence IoT), which achieves a high level of security and low consumption.

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  • WiFi (IEEE 802.11 b/g/n-compliant)
  • BLE 5 (mesh, Long range, PHY w/ 2Mbps support)
  • 32 bit LX 7
    • Dual core, up to 240MHz
    • Vector instructions, AI accelerator
  • Security
    • Flash encryption
    • Secure boot
    • Hardware cryptographic accelerators
  • Wide set of peripherals
    • 12 bit SAR ADC, temperature sensor, DAC
    • I2C, SPI, UART, TWAI, I2S
    • PWM 6 channel
    • DMA, SD/MMC



  • General IoT and AIoT applications
    • Home automation, voice controlled
    • Sensors
    • Thermostats
  • Bluetooth/WiFi medical equipment
    • Baby monitor, Health monitor
  • Wearable
    • Smart watch, fitness trackers
  • Smart agriculture


  • Combo WiFi+BLE5 with long range and mesh support
  • Extremely competitive price
  • Wide open source resources and documentation
  • Neural network support via ESP-WHO and ESP-Skainet frameworks.



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