
DFRobot FireBeetle 2 ESP32-P4 AI Development Kit
ESP32-P4 dual-core RISC-V AI development kit with hardware H.264 encoding at 1080p@30fps, MIPI CSI/DSI camera and display interfaces, ESP32-C6 WiFi 6 coprocessor, 32MB PSRAM, 16MB flash, PDM microphone, and IO expansion board.
$13.90
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Specifications
Components
Espressif ESP32-P4 with dual-core RISC-V at 360MHz, single-precision FPU, hardware H.264 encoding at 1080p@30fps, ISP, PPA, and 768KB L2 cache.
Companion ESP32-C6 handling WiFi 6 (802.11ax) and Bluetooth 5 LE connectivity, offloading wireless from the main P4 processor.
Built-in PDM microphone for audio capture, voice recognition, and speech processing applications.
Overview
The DFRobot FireBeetle 2 ESP32-P4 AI Development Kit (SKU: DFR1237) brings Espressif's most powerful MCU to an accessible $13.90 development platform. The ESP32-P4 features a dual-core RISC-V processor at 360MHz with a single-precision FPU, a 40MHz low-power core, and 768KB of L2 cache -- a significant step up from previous ESP32 generations in raw compute capability.
What sets the ESP32-P4 apart is its integrated media engine: hardware-accelerated H.264 video encoding at 1080p@30fps, a built-in Image Signal Processor (ISP), PPA graphics accelerator, and 2D-DMA. The board exposes MIPI CSI (2-lane) for cameras and MIPI DSI (2-lane) for displays, both using Raspberry Pi-compatible connectors for broad accessory support. An onboard PDM microphone adds audio capture for voice recognition applications.
Wireless connectivity comes via a companion ESP32-C6 coprocessor providing WiFi 6 (802.11ax) and Bluetooth 5 LE, keeping the main P4 cores free for media processing. The kit includes an IO expansion board that breaks out I2C, SPI, UART, I2S, ADC, touch, and PWM pins for prototyping. With 32MB PSRAM and 16MB flash, it has ample memory for AI inference, video buffering, and complex application logic. A TF card slot provides expandable storage for recording.
Use Cases
6Computer Vision
Image recognition, object detection, and ML inference using embedded cameras and AI-capable processors.
Video Streaming
Capturing and streaming video over WiFi or network, including IP camera feeds and real-time monitoring.
Voice Assistant
Offline and cloud-connected voice assistant, wake-word detection, and speech recognition projects.
Security Camera
WiFi-connected camera for surveillance, motion detection, and remote video monitoring.
IoT Dashboard
Display real-time IoT sensor data on an embedded screen for local monitoring.
Media Player
Building custom media playback devices for audio, video, or digital signage using DVI/HDMI output.
Resources
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