reComputer AI Lab | Edge AI Models & Tools
What is reComputer AI Lab?
reComputer AI Lab is an open platform for deploying edge-AI models on Seeed Studio reComputer hardware with a single Docker command. It brings together 100+ optimized computer-vision, LLM, and VLM models, a hardware toolchain for flashing and model conversion, step-by-step tutorials, and community projects — all tuned for reComputer devices built on NVIDIA Jetson, Rockchip RK3576/RK3588, and Raspberry Pi. Every model ships with benchmarks and a ready-to-run deployment command, so you can go from browsing to running inference at the edge in just two steps. Whether you are prototyping a vision application, running a local LLM, or shipping an industrial AI project, reComputer AI Lab lowers the barrier to real-world edge AI with reproducible, hardware-optimized workflows.
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Explore Models
CV, LLM, and VLM models ready to run on reComputer.
Browse all models →Tools
reComputer-optimized toolchain, one command to use.
Browse tools →Tutorials
Step-by-step guides and hands-on tutorials for reComputer.
Browse all tutorials →Community Projects
Share your community projects built on reComputer.
View all projects →Hot Model
Popular edge AI models ready to run on reComputer
Community Projects
View all projectsSee what the community is building with reComputer

Build a Real-Time Queue Counter with YOLO11 on reComputer RK3576
Turn a video or RTSP stream into a live queue monitor that counts people only inside the area you define, powered by YOLO11 on the RK3576 NPU.

Zone Alert with YOLO11 on reComputer RK3576
Monitor a camera, video, or RTSP stream and record an event when a person or car enters a user-defined zone, with YOLO11 inference accelerated by the RK3576 NPU.

RK3588 VPU and NPU Hardware Acceleration Benchmark
Reproducible MPP benchmarks for NV12-to-MJPG/H.264/H.265 hardware encoding, MJPG-to-YUV420 hardware decoding, and RKNN acceleration of YOLOv8n, YOLOv8s, and YOLOv8m inference on the reComputer RK3588.

