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reComputer RK3588-40, Open Rockchip AI Box tailored for AI Application Development
- Experience seamless edge AI development with this compact AI box, powered by the Rockchip RK3588 and 16GB RAM, designed for smart vision systems, AI agents, and more.
- Utilize the reComputer AI Lab for one-click AI application deployment, featuring optimized model demos, interactive tutorials, and extensive framework support.
Artikelnummer:
13169
Verfügbarkeit: Zur Zeit nicht an Lager
CHF 361.90
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Details
This product is more than an open-source 8-core Linux AI box. Built on the powerful Rockchip RK3588 16GB RAM, it is designed to make edge AI development and deployment faster and easier.
To improve the developer experience, Seeed offers reComputer AI Lab — a platform that helps you deploy AI applications with one-click tools and ready-to-use resources. It includes optimized edge AI model demos for CV, LLM, VLM, STT, and TTS, interactive tutorials, deployment tools, containerized applications, and community projects to speed up development on Rockchip.
With rich I/O, multiple OS support, wireless expansion options, and active cooling, this compact AI box is ready for a wide range of edge AI workloads.It is ideal for smart vision systems, voice-enabled devices, AI agents, robotics, and industrial edge applications.
Feature 1：Based on Powerful RK3588 Processor
The reComputer RK3588 features an advanced CPU architecture with
- 4 × Cortex-A76 @2.4GHz
- 4 × Cortex-A55 @1.8GHz
- LPDDR5 （8GB/16GB/32GB）
- ARM Mali GPU-G610 MC4
Feature 2：6 TOPS NPU Embedded
With a built-in 6 TOPS NPU, it delivers efficient AI inference directly on the device, reducing latency and enhancing privacy without relying on the cloud.
AI performance highlights include:
- Vision CNN: YOLO11@60FPS(640*640)
- LLM: capable for deepseek-r1-distill-qwen 7b support
- VLM: capable for qwen2.5-vl 3b
- STT: whisper_base_20s (RTF 0.215) with real-time processing support
- TTS：mms_tts_eng_200 （RTF 0.069) with real-time processing support
Check the details of the benchmark.
Feature 3：Compute Power & Storage & Wireless Connectivity Expandable
It offers flexible expansion through
a) 2 × M.2 M Key: PCIe 3.0 x4 and PCIe 2.1 x1, supports SSD expansion and AI accelerators such as Hailo and Rockchip， up to 26TOPS
b) 1 x miniPCIe for wireless expansion, like 4G LTE, LoRaWAN, Wi-Fi HaLow
Feature 4：Broad Model & Framework Support
It also supports a wide range of popular AI models, From computer vision and speech to LLM-powered edge intelligence, including: YOLO, MobileNet V2, RetinaFace, CLIP, Whisper, DeepSeek-R1, Qwen2-VL，...................
Framework support includes: ONNX, PyTorch, TensorFlow, TensorFlow Lite, Caffe, Darknet，...................
Toolchain support: RKNN-Toolkit2
This broad compatibility makes it easy to migrate existing models and build integrated edge AI applications across Perception AI, Generative AI, Agent and Physical AI.
Feature 5：Get Started in Seconds with reComputer AI Lab
Deploying AI at the edge is often complicated — from environment setup and model conversion to performance optimization. To simplify this process, Seeed created reComputer AI Lab, a developer platform designed to lower the barrier to edge AI development.
It provides a complete collection of optimized AI model demos for CV, LLM, and VLM, along with interactive tutorials, deployment tools, containerized AI applications, project examples, and community resources. It is built to accelerate AI development and deployment on Rockchip, Raspberry Pi, and NVIDIA Jetson platforms.
For Rockchip users, reComputer AI Lab includes ：
- Ready-to-Use Models
Access pre-optimized models without starting from scratch. AI Lab includes models such as YOLO11, MobileNet, CLIP, and Whisper, optimized for Rockchip platforms. With the RKLLM toolchain, it also supports edge LLM deployment.
- One-Command Deployment Tools
Skip complex build environments and speed up deployment with one-command tools. With Seeed-optimized RKNN-Toolkit2, models can be converted from ONNX to NPU deployment in just minutes, making AI application deployment faster and easier.
- Comprehensive Tutorials, Projects, and Community
From basic NPU benchmarking to real-world applications such as YOLO11-based industrial detection, AI Lab provides step-by-step guides, practical project examples, and community support to help developers build faster.
Feature 6： Pre-installed Armbian and Multi-OS
The device comes with Armbian pre-installed for a fast out-of-the-box experience.
With the help of Armbian, we are able to provide long-term maintained system images, security updates, encrypted OS options, and OTA upgrade support for production-ready deployment.
It also supports multiple operating systems through the Rockchip ecosystem, giving developers more flexibility across different projects, Ubuntu, Android, Debian.
Feature 7：Simultaneous 4-Display Output with 8K Video Capability
The reComputer RK35xx Series supports simultaneous 4-display output, giving developers more flexibility for digital signage, control centers, smart retail, and multimedia systems.
Supported output interfaces include:
- HDMI
- MIPI DSI
- Type-C (DP Alt Mode)
It also offers strong multimedia capabilities:
- Up to 8K@30fps video encoding with H.265 / H.264
- Up to 8K@60fps video decoding with H.265 / H.264 / AV1 / AVS2
This makes it ideal for high-resolution AI vision and multimedia applications.
Specification
| reComputer RK3576 | reComputer RK3588 | |
| SKU | 4GB RAM：100062096 8GB RAM：100052518 |
8GB RAM：100071234 16GB RAM：100086238 |
| CPU | 4x [email protected] 4x [email protected] |
4x [email protected] 4x [email protected] |
| GPU | ARM Mali-G52 MC3 | ARM Mali-G610 MC4 |
| NPU | INT8@6TOPS; Supporting INT4/8/16/FP16/BF16/TF32 mixed operations | |
| Operating System | Debian 12 | |
| RAM | LPDDR5: 4GB/8GB/16GB | LPDDR5: 8GB/16GB/32GB |
| Power Input | 9V-19VDC | |
| PoE (as powered device) | 1x PoE PD | 1x PoE PD |
| Button | 1x Power; 1x Recovery; 1x MaskROM | |
| Ethernet | 1x Gigabit Ethernet 1x Gigabit Ethernet with PoE support* |
1x 2.5 Gigabit Ethernet 1x 2.5 Gigabit Ethernet with PoE support* |
| USB | 1x Type A USB 3.0 3x Type A USB 2.0 1x Type C for OTG & DP |
4x Type A USB 3.0 1x Type C for OTG & DP |
| HDMI |
1x HDMI 2.0
|
2x HDMI 2.1;
1x HDMI 2.0 Input
|
| SIM Card | 1x nano SIM Card Slot | |
| SD Card | 1 x microSD card slot | |
| SSD Card | PCle2.1x 1 for NVMe SSD or Al Accelerator | PCle3.0x 4 for NVMe SSD or Al Accelerator PCle2.1x 1for NVMe SSD or Al Accelerator |
| LED | 1x Power; 1x Status; 1x User | |
| Buzzer | 1 | 1 |
| Wi-Fi | Onboard WiFi6 & BT5.4 with FPC Antenna | |
| BLE | ||
| LoRa | USB LoRa®*/SPI LoRa®* | USB LoRa®*/SPI LoRa®* |
| 4G/5G Cellular | 4G LTE* | 4G LTE* |
| Certification | FCC/CE/TELEC/RoHS | |
| Operating Temperature | 0~60°C | 0~55°C |
| Storage Temperature | -20~90 °C | -20~90 °C |
| Operating Humidity | 10~95% RH | 10~95% RH |
| RTC | 1x 2PIN | 1x 2PIN |
| Heat Dissipation | Heatsink with Fan | |
| Warranty | 1 year | |
Application
- Intrusion Detection
- Elderly Fall Detection
- Defect Detection
- Offline Voice Assistant
- On-Device Document Recognition
- Meeting Room Analytics
- Traffic Incident Detection
- Retail Shelf Monotoring
- Smart City Monotoring
Certification
| HSCODE | 8471504090 |
| USHSCODE | 8517180050 |
| UPC | |
| EUHSCODE | 8471707000 |
| COO | CHINA |
Part List
|
reComputer RK3588-40
|
x1
|
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12V/3A Power Adapter (with 1x US/EU/UK/AU Plugs)
|
x1
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32GB microSD Card
|
x1
|
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User Manual
|
x1
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