rockchip-linux/rknn-toolkit2

Health v2 · maintenance only

Adoption not part of the score

1193 stars · 179 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

RKNN-Toolkit2 is Rockchip's software development kit for converting trained AI models to RKNN format and deploying them on Rockchip NPU chips like RK3588 and RV1106. It includes PC-side model conversion and performance evaluation tools, Python deployment APIs, and a C/C++ runtime for on-device inference.

Use cases

• convert onnx models to run on rockchip npu
• deploy deep learning models on rk3588
• run inference on embedded ai hardware
• benchmark model performance on npu
• deploy computer vision models on rv1106

When to choose

• you are deploying AI models to Rockchip RK3566/RK3568/RK3588/RK3562 or RV1103/RV1106 chips
• you need to convert ONNX models to an NPU-optimized format
• you want C/C++ or Python inference APIs on Rockchip hardware

When to avoid

• you target older Rockchip chips like RK1808, RV1109, RV1126, or RK3399Pro (use rknn-toolkit instead)
• you need a maintained repository - this one has moved to airockchip/rknn-toolkit2
• you deploy to non-Rockchip hardware such as GPUs or other NPUs

Facets

library · maturity maintenance

machine-learning llm-inference sdk compiler machine-learning embedded-systems deep-learning hardware python cpp embedded npu rockchip model-conversion edge-ai rknn inference linux

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markdown · JSON · MCP: product_card(name="rockchip-linux/rknn-toolkit2")