ESP32-S3 vs ESP32-S2: AI and USB Features Compared

Espressif’s ESP32-S series has expanded rapidly, and two of the most popular members are the ESP32-S2 and ESP32-S3. While they share the same product family branding, these chips are quite different under the hood. If you are deciding between them for your next project — whether it’s a USB HID device, an AI-powered camera, or a wearable gadget — this deep-dive comparison will help you make the right choice.

1. Quick Overview: Key Specs at a Glance

2. CPU Architecture and Performance

Both chips use Espressif’s custom Xtensa LX7 core running at up to 240 MHz — a significant upgrade from the LX6 cores in the original ESP32. The LX7 brings improved pipeline efficiency, better branch prediction, and lower interrupt latency.

The critical difference: the ESP32-S2 is single-core, while the ESP32-S3 is dual-core. This matters enormously for multitasking. With FreeRTOS (the default RTOS for both chips), dual-core allows you to pin tasks to specific cores. For example, you can run Wi-Fi/networking on Core 0 and your application logic + AI inference on Core 1, with near-zero interference between them.

In benchmarks (Dhrystone, CoreMark), the ESP32-S3 dual-core outperforms the ESP32-S2 by roughly 1.7–1.9x in workloads that benefit from parallelism. For single-threaded tasks, the per-core LX7 performance is identical.

Bottom line for performance: If your application involves multiple simultaneous tasks — networking + display rendering + sensor processing — choose the ESP32-S3. For simpler, single-threaded USB devices or sensor nodes, the ESP32-S2 is adequate.

3. AI and Machine Learning Capabilities

This is where the ESP32-S3 truly distinguishes itself. Espressif added Paired Instruction Extensions (PIE) — a set of SIMD (Single Instruction, Multiple Data) vector instructions specifically for accelerating AI workloads like:

• Convolutional Neural Networks (CNNs) for image classification
• Keyword spotting and wake-word detection
• Gesture recognition from accelerometer data
• Face detection and recognition

Espressif’s ESP-WHO framework and TensorFlow Lite for Microcontrollers both leverage PIE instructions on the ESP32-S3. In practical tests, PIE accelerates neural network inference by 2–5x compared to running the same model on the ESP32-S2.

The ESP32-S2 has no hardware AI acceleration. You can still run TensorFlow Lite Micro on it, but inference is significantly slower and may not be fast enough for real-time applications like face detection at useful frame rates.

Verdict: For any project involving TensorFlow Lite, ESP-WHO, or real-time AI inference on the edge, the ESP32-S3 is the clear winner. The ESP32-S2 is not suitable for AI workloads beyond the simplest models.

Waveshare ESP32-S3 1.43inch AMOLED Display Development Board, 466×466

ESP32-S3 with a stunning 466×466 AMOLED round display — showcases the S3’s AI and graphics processing power in one compact board.

View on Zbotic

4. USB Features: OTG and USB Serial/JTAG

Both the ESP32-S2 and ESP32-S3 include a built-in Full-Speed USB 1.1 OTG controller — a feature the original ESP32 lacked entirely. This opens up exciting possibilities:

USB Device Mode (most common)

• CDC (Communication Device Class): Appear as a USB serial port — no CP2102 or CH340 bridge chip needed!
• HID (Human Interface Device): Emulate a keyboard, mouse, or gamepad.
• MSC (Mass Storage Class): Appear as a USB flash drive.
• WebUSB: Communicate directly with a browser via the WebUSB API.
• MIDI: USB MIDI instrument controller.

USB Host Mode (ESP32-S3 advantage)

The ESP32-S3 can also operate in USB Host mode, which allows it to control USB devices connected to it — a USB keyboard, barcode scanner, RFID reader, or even a USB thumb drive (with TinyUSB’s MSC host driver). The ESP32-S2 has more limited host support in practice.

USB Serial/JTAG

Both chips include a built-in USB Serial/JTAG controller (separate from the OTG). This means you can flash firmware and debug over a single USB cable without any external USB-to-serial converter. This significantly simplifies PCB design and reduces component count for production products.

USB summary: For pure USB device applications (HID, CDC, MIDI), both chips are equivalent. For USB host functionality, the ESP32-S3 with its mature TinyUSB host stack is the better choice.

5. Wireless Connectivity

Here is perhaps the most dramatic difference: the ESP32-S2 has Wi-Fi only, with absolutely no Bluetooth support. The ESP32-S3 adds Bluetooth 5.0 + Bluetooth Low Energy.

This might seem like a minor point, but it has major implications:

• ESP32-S2: Cannot connect to Bluetooth devices, cannot act as a BLE beacon, cannot be configured via a smartphone Bluetooth app. Wi-Fi provisioning must be done over the network.
• ESP32-S3: Full BT 5.0 + BLE. Can use ESP-IDF’s Bluedroid or NimBLE stack. Supports BLE advertising, scanning, GATT server/client, Bluetooth Classic audio (A2DP), and ESP-BLE-MESH. Works with Espressif’s ESP BLE Provisioning for easy Wi-Fi setup via a smartphone app.

If your project needs to communicate with a smartphone, fitness band, BLE sensor, or any Bluetooth peripheral, the ESP32-S2 is a non-starter. Go with the ESP32-S3.

6. GPIO Count and Peripherals

The ESP32-S3 has 45 GPIO pins vs 43 on the ESP32-S2. Both support capacitive touch sensing on 14 pins. Both have the same complement of standard peripherals: SPI, I2C, I2S, UART, CAN (TWAI), RMT, LEDC PWM, ADC (12-bit), DAC, and a pulse counter.

Key peripheral differences:

• LCD interface: ESP32-S3 adds support for RGB565 parallel display interface, enabling it to drive larger colour LCDs directly without an external driver chip.
• I2S: ESP32-S3 has enhanced I2S with better support for TDM audio.
• SPI: Both have 4 SPI controllers; ESP32-S3 SPI in slave mode supports GP-SPI DMA transfers up to 80 MHz.

7. Memory: RAM and Flash

The ESP32-S3 wins on memory too:

• SRAM: 512 KB vs 320 KB on the S2. Extra 192 KB matters for TensorFlow Lite model buffers and large image frame buffers.
• ROM: 384 KB vs 128 KB. More ROM means more functionality available without consuming flash.
• PSRAM: Both chips support external Octal PSRAM (up to 8 MB). The ESP32-S3 supports faster Octal-SPI PSRAM at 80 MHz vs 40 MHz on the S2 in some configurations — this is critical for rendering images and running AI models that don’t fit in internal SRAM.

Waveshare ESP32-S3 1.46inch Round Display Development Board, 412×412

Compact wearable-style board with ESP32-S3, round 412×412 display, accelerometer, gyroscope, speaker and microphone — ideal for AI voice projects.

View on Zbotic

8. Power Consumption

Both chips are low-power variants of the ESP32 family, with no Ethernet MAC and reduced peripheral set compared to the original ESP32. Typical power figures:

Interestingly, the ESP32-S3 achieves lower deep sleep current (7 µA vs 22 µA) despite having more features. This is a result of architectural improvements in the power management unit. For battery-powered IoT sensors that spend most of their time sleeping, the ESP32-S3 may actually last longer on a battery.

9. Display and Camera Support

Both chips support a parallel DVP camera interface for connecting OV2640 or similar camera modules. However, the ESP32-S3 handles camera + AI pipelines much better due to its dual core and AI acceleration — it can capture a frame, run face detection, and still maintain a Wi-Fi connection simultaneously.

For displays, the ESP32-S3’s enhanced LCD controller supports RGB565 interface, making it compatible with a broader range of affordable colour TFT panels without needing an SPI-to-parallel bridge. This is what enables products like the Waveshare ESP32-S3 AMOLED boards.

Waveshare ESP32-S3 1.47inch 172×320 LCD Display Development Board

Slim ESP32-S3 board with a 262K-colour LCD — great for learning display programming with the S3’s enhanced graphics capabilities.

View on Zbotic

10. Which Chip Should You Choose?

Choose ESP32-S2 if:

• You need USB HID/CDC/MSC device functionality and don’t need Bluetooth.
• Your application is single-threaded and doesn’t require parallel processing.
• You want the absolute lowest cost in the Espressif USB-capable lineup.
• You are building a simple Wi-Fi sensor node, USB gadget, or web server device.
• Power consumption in deep sleep is not critical (though actually S3 wins here too).

Choose ESP32-S3 if:

• You need Bluetooth or BLE — period. The S2 cannot do this.
• Your project involves AI inference — face recognition, keyword spotting, gesture detection.
• You need dual-core performance for multitasking (networking + AI + UI simultaneously).
• You are building a camera-based project (ESP-WHO, face recognition, QR code scanner).
• You need more RAM for complex applications, large frame buffers, or machine learning models.
• You want USB host mode to connect USB peripherals to your project.

In most new designs, we recommend the ESP32-S3 as the default choice — the extra cost is marginal, and you get Bluetooth, dual-core, AI acceleration, and more RAM. The ESP32-S2 remains valuable for cost-sensitive, USB-only applications where Bluetooth is not needed.

11. Development Boards Available in India

Ai Thinker ESP32 CAM Development Board WiFi+Bluetooth with AF2569 Camera Module

Complete ESP32 camera board — perfect for learning face recognition and AI vision before upgrading to the ESP32-S3 platform.

View on Zbotic

Frequently Asked Questions

Conclusion

The ESP32-S3 vs ESP32-S2 debate has a clear answer for most projects: unless you specifically need a low-cost USB-only solution without Bluetooth, the ESP32-S3 is the better choice. Its dual-core LX7, AI vector instructions, Bluetooth 5.0, larger memory, and lower deep sleep power make it a genuine upgrade worth the modest extra cost.

The ESP32-S2 still has its place in USB HID gadgets, low-cost Wi-Fi sensors, and any application where Bluetooth is genuinely not needed. But for AI-powered projects, camera applications, and anything involving a smartphone connection, the ESP32-S3 is the chip you want.