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Powered By Luckfox Core3576 Module To Enable AI Edge Computing,
Making It Easy For You To Explore The World Of AI
Processor | Quad-core Arm [email protected] + Quad-core Arm [email protected] |
RAM | Options for 4 / 8GB LPDDR4X RAM |
eMMC | Options for 0 / 32 / 64GB eMMC Flash |
NPU | 6 TOPS@INT8, supports INT4, INT8, INT16, FP16, BF16, TF32 mixed operation |
GPU | ARM Mali G52 [email protected], supports OpenGL ES 1.1/2.0/3.2, OpenCL 2.0 and Vulkan 1.1, built-in high-performance 2D/3D acceleration hardware |
ISP | Built-in 16MP ISP, supports multiple algorithm accelerators such as HDR, 3A, CAC, 3DNR, 2DNR, Sharpening, Dehaze, Enhance, Debayer, and small-angle lens distortion correction, etc. |
Video | Decoding: 4K@120fps (H.265/HEVC, VP9, AVS2, AV1); 4K@60fps (H.264/AVC) |
Encoding: 4K@60fps (H.265/HEVC, H.264/AVC) | |
Storage | TF card slot |
M.2 connector × 1 (PCIe NVMe SSD support, compatible with 2242/2260/2280 size) | |
Connectivity | 1000M Ethernet port × 2 |
Onboard wireless module supporting 2.4GHz/5GHz dual-band Wi-Fi6 and Bluetooth 5.2/BLE | |
Video Output | HDMI2.1 (4K@120fps) port × 1 |
4-lane MIPI DSI (2K@60fps) interface × 1 | |
Video Input | 4-lane MIPI CSI camera interface × 2 |
USB | USB Type-C (5Gbps/DP) × 1, supports OTG and image burning |
USB3.2 Gen1 port (5Gbps) × 1 | |
USB2.0 port × 3 | |
CAN | Supports high-speed CAN FD and CAN2.0A/B data communication. |
Audio | Onboard microphone |
3Pin MX1.25 audio output header | |
GPIO | 40Pin GPIO header (compatible with most Raspberry Pi HATs) |
System Support | Buildroot, Debian, Ubuntu, Android 14 |
Power input | 5V DC |
Ambient temperature | Operating temperature: 0°C ~ 60°C Storage temperature: 0°C ~ 70°C Storage humidity: 10% ~ 90%RH (no condensation) |
Others | Onboard IR receiver with 38KHz carrier frequency |
2Pin SH1.0 RTC battery header | |
5V fan header |
Equipped with high-performance RK3576 processor, integrated with quad-core Cortex-A72 and quad-core Cortex-A53, providing strong performance and high energy efficiency
Equipped with 6 TOPS computing power, easy to convert a variety of neural network models based on TensorFlow, MXNet, PyTorch, and Caffe frameworks.
Object Recognition
Face Recognition
Vehicle Recognition
Pedestrian Detection
Text Recognition
Semantic Segmentation
Supports 4K@120fps (H.265/HEVC, VP9, AVS2, AV1), 4K@60fps (H.264/AVC) decoding and 4K@60fps (H.265/HEVC, H.264/AVC) encoding, easy to deal with HD video tasks
Different types of traffic can be distributed to different network interfaces: one for external Internet connection and another for internal LAN, which improves security and management flexibility
Suitable for vision robotics, depth vision, stereo vision and other AI vision applications
Widely used in edge computing, local deployment of large models, intelligent commercial displays, cloud terminal products, industrial control hosts, automotive electronics, and more
Weight: 0.039 kg
Quick Overview
OPTIONS Core3576 Edge Computing Development Board (including Core3576 Module) x 1