ESP32 vs ESP32-S3: Key Differences, Performance Comparison, and PCB Design Considerations

Since the ESP32 series entered the market, it has reshaped the landscape of embedded development and the Internet of Things. The ESP32 microcontroller became widely adopted thanks to its exceptional price-to-performance ratio, strong ecosystem, low power consumption, solid performance, and rich peripheral interfaces.

However, as IoT applications evolved and demand for AI, vision, and high-speed connectivity increased, the classic ESP32 began showing limitations in advanced scenarios. To address these new requirements, Espressif introduced the ESP32-S3, targeting AIoT and performance-oriented applications.

This article provides a detailed ESP32 vs ESP32-S3 performance comparison, highlights their functional differences, and outlines essential PCB design considerations for engineers. The goal is not to determine which MCU is universally better, but to help developers choose the right chip based on project requirements.

Core Performance Comparison: ESP32 vs ESP32-S3

CPU Architecture: Xtensa LX6 vs Xtensa LX7

ESP32

• Cores: Dual-core
• Architecture: Xtensa LX6
• Clock Speed: Up to 240 MHz
• Key Traits: The LX6 CPU delivers robust general-purpose computing, enabling the ESP32 to simultaneously handle Wi-Fi/Bluetooth stacks and user applications—one reason it became the default choice in many IoT projects.

ESP32-S3

• Cores: Dual-core
• Architecture: Xtensa LX7
• Clock Speed: Up to 240 MHz
• Upgrade Highlights: LX7 introduces enhanced memory access and powerful vector instructions, significantly boosting ESP32-S3 performance in digital signal processing and lightweight machine learning tasks.

Real-World Performance Impact

Even at the same frequency, LX7 achieves higher instructions per cycle and improved energy efficiency. This means the ESP32-S3 completes tasks faster and consumes less energy per operation.

Multitasking Comparison

Both MCUs run FreeRTOS effectively, but the ESP32-S3 offers better responsiveness and lower latency under high workloads due to architectural improvements.

AI and Image Processing Capabilities

AI Vector Instruction Advantage of ESP32-S3

The ESP32-S3 Xtensa LX7 CPU core integrates a powerful vector instruction set, which is a key highlight in the ESP32 vs ESP32-S3 performance comparison. This instruction set can process multiple data in a single cycle, achieving single-instruction multiple-data (SIMD) parallel computation, and is a major ESP32-S3 performance advantage for AI tasks. Compared to the traditional ESP32 microcontroller that relies on general-purpose CPU software computation, these specialized instructions can perform matrix multiplications, convolutions, and other AI core operations several to tens of times faster while significantly reducing power consumption, demonstrating the ESP32-S3 microcontroller advantages for PCB engineers in AIoT projects.

AI Inference Performance

• ESP32: Limited to extremely lightweight models (<1 FPS), with lower accuracy and practicality.
• ESP32-S3: Can run TensorFlow Lite Micro–based face detection at ~10+ FPS, support multi-keyword wake-word models, and enable low-latency responses.

Application Impact

• Smart Doorbell / Camera:

ESP32: Basic motion detection

ESP32-S3: Real-time face detection or recognition

• Smart Appliances:

ESP32: Basic connectivity and control

ESP32-S3: Vision-based behavior (e.g., fabric recognition in washing machines)

RAM and Flash differences

Internal RAM

• ESP32: ~520 KB SRAM
• ESP32-S3: 512 KB SRAM + 384 KB ROM + RTC memory

PSRAM Support

Both support external PSRAM (commonly 8MB), but the ESP32-S3 more broadly supports Flash + PSRAM combo packages—beneficial for compact MCU PCB layout designs.

Flash Requirements

Both the ESP32 and ESP32-S3 support external SPI Flash up to 16MB, providing ample space for large programs and data. AI model files typically occupy several hundred KB to a few MB of Flash. When using the ESP32-S3, it is recommended to select a larger Flash capacity (above 4MB) to accommodate these models. The ESP32 microcontroller does not have strict Flash requirements

Peripheral Interfaces and Connectivity

USB 2.0 OTG (S3 Only)

The ESP32-S3 features native USB OTG, enabling:

• USB HID (keyboard, mouse)
• USB camera
• USB CDC (virtual COM)
• Firmware download without a USB-to-UART bridge

This eliminates extra components and simplifies PCB design.

LCD & Camera Interfaces (S3 Only)

• Dedicated LCD controller (RGB/I8080/SPI)
• Parallel camera interface (DCMI)

These interfaces are crucial for vision and HMI applications—capabilities the classic ESP32 lacks.

Traditional Peripherals

• ESP32: 4× SPI, 2× I2C, 2× UART, 34 GPIO
• ESP32-S3: More GPIO (45), additional UART, improved SPI support

Wireless Performance

Both the ESP32 and ESP32-S3 support 802.11 b/g/n Wi-Fi 4 operating at the 2.4GHz frequency band. However, the ESP32-S3 features enhanced RF circuitry, providing improved reception sensitivity, better interference immunity, and higher maximum throughput, resulting in more stable connections and faster data rates.

Both microcontrollers support BLE 5, but the ESP32-S3 offers superior stability.

Power Consumption and Energy Efficiency

Idle Power

The ESP32-S3 typically offers equal or slightly better energy efficiency under light workloads.

Deep Sleep

Both the ESP32 and ESP32-S3 have similarly low power consumption, around 10 μA, which is crucial for achieving long standby times in battery-powered devices. Compared to the ESP32, the ESP32-S3 offers greater flexibility in low-power operation.

High Load Power

Under prolonged high-load operation, the classic ESP32 consumes more power and generates more heat. The ESP32-S3, thanks to its higher execution efficiency with the LX7 architecture, can complete the same tasks faster and return to sleep mode sooner, resulting in lower average power consumption. While the peak power of both MCUs is similar, the S3 has a lower “energy per task” metric.

Implications for Battery-Powered Devices

• ESP32: Best for cost-sensitive designs with moderate power requirements.
• ESP32-S3: Best for intermittent AI, periodic sensing, always-connected devices, long battery life.

Module & Packaging Comparison

ESP32

• Size: 18 × 25.5 × 3.1 mm
• Flash: 4MB
• GPIO: 34 pins
• Antenna: PCB or U.FL

Its metal shield design is simple and practical, but the RF interference immunity is relatively weak. It is compatible with many mature solutions and serves as the “default choice” for general IoT projects.

ESP32-S3 Modules

• Size: 18 × 20 × 3.1 mm
• Flash: Up to 8MB + 2MB PSRAM
• Optimized RF performance & EMI shielding

Its packaging and interfaces are better suited for high-performance and vision-based applications.

Package Size, Antenna Performance, and Shielding Differences

• Size: Both modules are similarly compact, but some ESP32-S3 variants have slight differences due to PSRAM/Flash configurations.
• Antenna Performance: The ESP32-S3 series optimizes antenna matching circuits, improving reception sensitivity by approximately 3 dB, resulting in more stable connections in complex environments.
• Shielding Design Differences: Both use metal shields, but the ESP32-S3 provides better EMI control, making it more suitable for dense high-speed peripheral designs.

Supply Lead Time and Price Comparison

• Supply Lead Time: ESP32 production capacity is stable, ensuring reliable supply; S3 series, due to added PSRAM and advanced packaging, may experience more inventory fluctuations.
• Price: ESP32 modules are generally lower in cost, while ESP32-S3 modules are slightly more expensive due to higher performance and enhanced features.

PCB Design Considerations

This section addresses how ESP32 vs ESP32-S3 differences affect PCB design.

Power Design

Both the ESP32 and ESP32-S3 require a clean and stable 3.3V power supply, using high-quality LDOs or DC-DC regulators.

• Peak Current: Both can reach 500–700 mA during Wi-Fi transmission, while the ESP32-S3 may experience higher peaks in high-speed USB or camera applications.
• Decoupling Capacitors: Place a combination of 100 nF + 4.7 µF decoupling capacitors near the power pins to filter noise at different frequencies. For ESP32-S3, with its higher clock speed and more complex peripherals (USB, PSRAM), power integrity requirements are stricter, and capacitors should be positioned as close as possible to the relevant pins.
• Minimized Power Loops: Keep short ground paths to reduce noise and improve wireless stability.
• Power Architecture Recommendation: Prefer using DC-DC converters to improve efficiency and avoid relying solely on LDOs, which can cause heat buildup and lower efficiency.

RF Antenna Layout

• all need 50Ω impedance
• Keep antenna area clear (≥15mm)
• Reserve π matching network (Usually C-L-C)

The ESP32-S3 features optimized RF performance, which also makes it more sensitive to matching circuits. It is highly recommended to strictly follow the official module reference design.

USB PCB Routing (S3 Only)

Since the ESP32 itself does not have a native USB interface, only the USB routing requirements for the ESP32-S3 are discussed.

• Differential Pair: The USB D+ and D– signals must be routed as a 90Ω ± 10% differential pair.
• Length Matching and Parallel Routing: The USB D+ and D– differential lines must be kept equal in length and routed closely in parallel to minimize skew.
• Keep Away from Noise Sources: USB differential lines should be routed away from oscillators, switching power supplies, and RF traces to reduce interference.

Camera/LCD High-Speed Routing (S3 Only)

• Strict length matching (±25 mil)
• Keep traces short
• Consider EMI filtering if a camera is used

SPI Flash & PSRAM Routing

• Length matching across CLK and data lines
• Optional 22–33Ω series resistors for signal integrity
• More critical for S3 under AI/vision workloads

Thermal Design

• Provide copper area under module
• Avoid sealed enclosures
• Prefer DC-DC over LDO to reduce heat

Recommended Application Scenarios

When to Choose ESP32

The classic ESP32 is a well-proven, cost-effective solution, ideal for applications with clear functionality, cost sensitivity, and no need for advanced AI capabilities. If the project goal is “low cost + stable connectivity,” ESP32 offers the best value, with abundant development resources, very low cost, and a stable supply chain. Suitable projects include:

• Smart switches, sockets, and lighting control
• Wi-Fi sensor nodes (temperature, humidity, smoke, environmental monitoring)
• General gateway devices and repeaters
• Wearables, fitness bands, and simple control panels
• Small motor or relay control systems

When to Choose ESP32-S3

The ESP32-S3 is a future-oriented AIoT microcontroller, ideal for projects requiring stronger local processing power, dedicated peripherals, or edge intelligence. If the project goal is “high performance + AI/vision + high-speed peripherals,” the S3 is clearly superior. Suitable projects include:

• Facial recognition access control and attendance terminals
• AIoT camera modules and image acquisition devices
• USB HID/CDC and camera-based devices
• Edge AI inference nodes (object detection, gesture recognition)
• Smart devices requiring LCD displays
• High-speed sensor data processing (industrial inspection, vision robots)

Selection Strategy

• Cost + simplicity + stability → ESP32
• Performance + AI/vision + advanced peripherals → ESP32-S3

Conclusion

By clearly understanding the differences between the ESP32 and ESP32-S3 and how these variations impact hardware design, engineers can make informed chipset selections that match their project requirements. Applying the correct PCB design practices ensures better performance, higher reliability, and a smoother development process for next-generation IoT devices.