Tencent/ncnn
ncnn is a high-performance neural network inference framework optimized for the mobile platform
From the publisher
README & documentation
Source previewRead the project’s overview, installation instructions and usage examples. The original README is the source of truth.
[](LICENSE.txt) [](https://github.com/Tencent/ncnn/releases) [](https://codecov.io/gh/Tencent/ncnn) ncnn is a high-performance neural network inference framework optimized for mobile, embedded, and desktop deployment. It has no third-party runtime dependencies, runs across CPU and Vulkan GPU backends, and provides tools such as pnnx for converting PyTorch and ONNX models to ncnn. Developers can deploy deep learning models efficiently on phones, PCs, browsers, and edge devices. ncnn is currently being used in many Tencent applications, such as QQ, Qzone, WeChat, Pitu, and so on. ncnn 是一个面向移动端、嵌入式和桌面端部署优化的高性能神经网络推理框架。 ncnn 无第三方运行时依赖，支持 CPU 和 Vulkan GPU 后端，并提供 pnnx 等工具将 PyTorch 和 ONNX 模型转换为 ncnn 模型。 基于 ncnn，开发者可以将深度学习模型高效部署到手机、PC、浏览器和边缘设备上。 ncnn 目前已在腾讯多款应用中使用，如：QQ，Qzone，微信，天天 P 图等。 The recommended beginner path is PyTorch -> pnnx -> ncnn. Install pnnx in a PyTorch environment Export a PyTorch model to ncnn This generates model.ncnn.param and model.ncnn.bin. Run with ncnn C++ API Or use Python See pnnx, use ncnn with PyTorch or ONNX, Python API, and examples for complete workflows.…
Read the full README ↗ · Preview checked 2026-10-27T06:18:21.355Z
Inside the original README — Document outline
- ncnn
- Quick Start
- Community
- Download & Build status
- Build
- Model Conversion
- Features
- Model and Workload Coverage
- Project Examples
- Documentation And FAQ
- License
Headings are captured from the source. Links open the publisher’s document, not a locally hosted copy.
Links from the README
References supplied by the publisher, not independently verified endorsements. Check the destination before downloading files or entering credentials.
Documentation belongs to its respective authors. Reported project/model license: Other. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
What this repository does
ncnn is a high-performance neural network inference framework optimized for the mobile platform
Repository facts
- Owner
- Tencent
- Primary language
- C++
- Stars
- 24,014
- Forks
- 4,535
- Open issues + pull requests
- 1,293
- License
- Other
- Archived
- No
- Default branch
- master
- Created
- 2017-06-30T10:55:37.000Z
- Last push
- 2026-10-30T11:26:42.000Z
Topics and intended use
Owner-supplied topics: android, arm-neon, artificial-intelligence, caffe, darknet, deep-learning, high-preformance, inference, ios, keras, mlir, mxnet, ncnn, neural-network, onnx, pytorch, riscv, simd, tensorflow, vulkan
Review the README for scope, installation, examples and limitations. We do not run repository code or certify it.
Evaluate before installing
Review licensing and dependencies, inspect recent commits and unresolved issues, and test in an isolated environment before production use. Stars and forks alone cannot answer these questions.
Source and freshness
Source: GitHub. Metadata observed 2026-11-01T13:20:54.848Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.