RK3576 + RK1828 Edge AI Development Kit for Local LLM, VLM & Vision (20 TOPS AI Accelerator, 5GB DRAM & IMX415 Camera)

The RK3576 + RK1828 AI Development Kit combines an RK3576 host with a 20 TOPS RK1828 AI coprocessor featuring 5GB dedicated DRAM and up to 1TB/s memory bandwidth for edge AI development and evaluation.

The RK3576 and RK1828 hardware and software environment has been tested by DFRobot, reducing the work required for host selection and compatibility testing. The platform supports LLM, VLM, speech and computer vision workloads for robotics, industrial vision and intelligent edge devices.

20 TOPS AI Acceleration with 5GB Dedicated High-Bandwidth Memory

The RK1828 is a dedicated AI coprocessor designed for edge inference workloads. It provides 20 TOPS INT8 AI computing performance and integrates 5GB of dedicated DRAM with up to 1TB/s memory bandwidth, providing dedicated compute and memory resources for large language, vision-language and computer vision models.

The available RK1828 model ecosystem includes models such as Qwen3-8B, Qwen2.5-7B, Qwen2.5-VL-7B, InternVL, Gemma, Whisper, DINO, SigLIP and YOLO, enabling developers to evaluate workloads ranging from local conversational AI to visual understanding and real-time vision inference.

Skip Host Selection and Compatibility Testing

An AI accelerator is only useful when the host platform, PCIe interface, power system, drivers and software environment work together. With a standalone RK1828 module, developers need to verify whether their existing host provides a compatible M.2/PCIe interface, suitable power delivery and supported software environment.

This kit pairs the RK1828 with a validated RK3576 development platform, giving developers a known hardware configuration for evaluating the accelerator.

RK3576

This allows engineering teams to spend less time troubleshooting host compatibility and more time evaluating AI performance and developing applications.

Broad Model Support across LLM, VLM, Speech and Vision

The RK1828 software ecosystem covers multiple major edge AI workload categories, allowing developers to evaluate different model architectures using the same accelerator platform.

With pre-converted model resources and RKNN3 deployment workflows available for supported models, developers can begin evaluation without building every model conversion and quantization workflow from scratch.

Move from Hardware Setup to Working AI Examples Faster

The platform provides tested driver resources, model files and application examples designed to shorten the path between installing the hardware and seeing a working AI result.

DFRobot provides RKNN examples and software resources covering workloads such as YOLO object detection, instance segmentation, pose estimation, CLIP image-text matching, Whisper speech recognition, TTS, OCR and multimodal inference.

For RK1828 workloads, supported model and demo resources are provided through the product documentation. Once the required driver and model resources are prepared, provided examples can be launched directly instead of requiring developers to build an application from scratch.

An Integrated Edge AI Prototyping Platform

The RK3576 host platform provides the connectivity and interfaces required to turn AI inference into a working application prototype.

Kit Platform

This allows developers to connect cameras, displays, communication modules, sensors and other peripherals when moving from model evaluation to application prototyping.

Start Vision AI Development with an Included Camera

An IMX415 camera module is included with the kit, providing developers with a hardware input for testing computer vision workloads.

Combined with the RK3576 camera interfaces and available YOLO, OCR, face detection and vision-language examples, the camera can be used to evaluate visual perception pipelines without selecting a separate camera module first.

Rockchip RK1828 Performance Reference

Reference Performance across LLM, VLM and Vision Workloads

Performance Note: The figures above are Rockchip reference benchmark results for the RK1828. The published benchmark platform uses RK3588 + RK1828 PCIe unless otherwise specified. Actual performance on the RK3576 + RK1828 kit may vary depending on the model, software version, configuration and workload.