nndeploy/nndeploy

Health v2 · maintenance only

Adoption not part of the score

1868 stars · 233 forks observed · 2026-08-28

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

nndeploy is an easy-to-use, high-performance AI deployment framework written in C++ with Python bindings. It provides a visual drag-and-drop workflow for building AI pipelines that can be exported as JSON and deployed across desktop, mobile, edge devices, and servers using multiple inference backends like TensorRT, ONNX Runtime, OpenVINO, and MNN.

Use cases

• deploy deep learning models on edge devices like Jetson and Ascend
• build AI pipelines with a drag-and-drop visual workflow
• run LLMs and diffusion models with a node-based interface
• export an AI workflow as JSON and call it from C++ or Python
• deploy the same model across Windows, Android, iOS, and Linux
• switch inference backends like TensorRT, OpenVINO, or ONNX Runtime without rewriting code
• write custom preprocessing nodes in Python or high-performance nodes in C++/CUDA

When to choose

• you need to deploy AI models across heterogeneous hardware (desktop, mobile, edge, server)
• you want a visual, low-code workflow for composing AI pipelines
• you need multi-backend inference support without vendor lock-in
• you are deploying LLMs or AIGC models and want a workflow-based tool
• you want workflows exportable as JSON for production integration

When to avoid

• you only need a single-backend inference runtime with a mature ecosystem like TensorRT alone
• you need a battle-tested framework with large community support like ONNX Runtime or TFLite
• your project is pure training rather than deployment
• you require extensive third-party integrations beyond what the framework currently offers

Facets

framework · maturity active

machine-learning llm-inference workflow-automation deployment gpu-computing developer-tools deep-learning large-language-models machine-learning developer-tools cross-platform windows python cpp cross-platform ai-deployment inference-engine visual-workflow low-code tensorrt onnxruntime openvino mnn edge-deployment stable-diffusion linux macos android ios gpu

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markdown · JSON · MCP: product_card(name="nndeploy/nndeploy")