The evolution speed of domestic AI chips has far exceeded imagination. Following the RK3588, Rockchip has launched a brand-new platform—the RK3576. It is lighter, more efficient, and more powerful, emerging as the new "performance benchmark" for next-generation AI edge computing. This article provides a comprehensive analysis of this rising domestic AI star—from core module to development board.

From RK3588 to RK3576 – a new performance gradient for domestic AI chips  

Balancing compute and power has always been central to edge-AI hardware; Rockchip’s RK3576, launched after RK3588, fills out a fuller performance ladder and covers every tier of AI endpoints.

Typical Application Scenarios,Mid-range industrial tablets, robots, UFS expansion needs, AI scenarios requiring 4K video and 6 TOPS NPU,High-end edge AI, 8K video processing, multi-task concurrency, smart cameras, industrial inspection, and other scenarios with extremely high demands on compute and bandwidth.

RK3588: Stronger compute (A76 + A55, dual-channel wide-memory, 8K codec, triple-core NPU), suitable for high-end products with extreme requirements on performance, video resolution, and parallel AI inference.

RK3576: Significant advantages in cost and power, still offers 6 TOPS NPU and 4K video, ideal for budget-constrained, power-sensitive mid-range embedded devices.

RK3576 maintains the high-spec 6 TOPS NPU while offering better power and package-size benefits—making it a better fit for edge computing, AI endpoints, smart industry, in-vehicle control, and other scenarios demanding high energy efficiency.

LCH3576 Core Module: a 42 mm domestic-performance heart

Built on Rockchip RK3576, the LCH3576 core module measures only 42 mm × 42 mm yet remains fully featured. It uses castellated pads plus LGA packaging for high reliability, low cost and flexibility, exposing LCC 160-pin + LGA 148-pin signals that cover display, camera, audio, network and storage interfaces.

SoC: Octa-core 64-bit (4×A72 @ 2.2 GHz + 4×A53 @ 1.8 GHz)

GPU: Mali-G52 MC3, 2-D graphics engine, dual-core RGA, VDPP, VPSS, 16 M ISP, JPEG encode/decode

NPU: 6 TOPS; supports int4/int8/int16/FP16/BF16/TF32

VPU: decode 8K@30 fps / 4K@120 fps (H.265/HEVC, VP9, AVS2, AV1) and 4K@60 fps (H.264/AVC); encode 4K@60 fps (H.265/HEVC, H.264/AVC)

DDR: LPDDR4/4X/5, options 2 GB / 4 GB / 8 GB / 16 GB

eMMC: eMMC 5.1, options 16 GB / 32 GB / 64 GB / 128 GB

PMU: RK806

OS: Android / Ubuntu / Buildroot / Debian / OpenEuler / Kylin

“A 42 mm module that powers the whole platform’s compute heart.” This lets LCH3576 move straight from prototype to industrial volume production, giving developers an instant AI boost without redesigning the mainboard and slashing iteration cost.

LKD3576 Dev Board: full interfaces, beyond-expectation experience  

As the official eval platform for LCH3576, the board’s interface set is close to exhaustive:

- Power: DC 12 V / 3 A  

- Network: 2× 1000 Mb Ethernet  

- USB: 3× Type-A USB 3.0 + 1× Type-C (debug)  

- Cameras: 3× 4-lane MIPI-CSI  

- Display: 1× HDMI 2.0 + 1× MIPI-DSI (touch support)  

- Audio: MIC in, headphone in/out, stereo speaker out  

- Wireless: FD7352S dual-band Wi-Fi 6 & BT 5.4  

- Expansion: mini-PCIe (4G/5G) + M.2 (2242 SSD)  

- Industrial: UART, CAN-FD, RS485  

Real-world test: three MIPI cameras plus touch display running concurrently—smooth, low latency, cool temps. NPU keeps stable throughput under multi-model loads while holding power low. Performance is solid, but the bigger surprise is rock-solid stability and dev-friendly convenience.

From module to finished unit: one-stop AI edge platform  

Another highlight of the RK3576 platform is its complete ecosystem support.  

- For both core module and dev board, Neardi delivers matching SDKs, firmware and WIKI tutorials that take developers from first power-on to AI deployment in minutes.  

- ✅ SDK: Android, Ubuntu, Debian, Buildroot, Kylin, OpenEuler  

- ✅ AI frameworks: TensorFlow, ONNX, PyTorch—one-click conversion  

- ✅ Tool-chain: RKNN-Toolkit3 for model conversion and performance tuning  

- ✅ Docs: open WIKI, continuously updated cases and demos  

In short, LCH3576 + LKD3576 is more than hardware—it is a ready-to-run AI edge package.

Application outlook: RK3576 is opening more AI scenarios  

With flexible performance, high-TOPS NPU and low power, RK3576 is now deployed across many industries, giving embedded-AI developers a faster, stabler hardware base. It handles single-device compute and also complex multimodal AI, putting AI terminals into every vertical.

Smart terminals  

- AI vision box, smart IPC, intelligent access control  

- Face, action and behavior recognition in real time  

- Multi-camera inputs with high frame rate and low latency  

Industrial control & manufacturing  

- Machine-vision inspection, defect detection, edge node  

- Real-time monitoring and alarm in smart factories  

- Multi-sensor fusion for higher automation and quality, fit for 24/7 plants  

Automotive & IoT endpoints  

- Smart cluster, in-car DVR, AVM surround-view  

- Edge AI for driver behavior, environment sensing, safety alerts  

- With 4G/5G modules, enables remote upload and real-time analytics