Paddle

PaddlePaddle is Baidu's deep learning framework, in the same category as PyTorch and TensorFlow. It is a full platform for building, training, and deploying models, with unified dynamic and static graphs, automatic parallelism for large-model training, and deployment tooling across a wide range of hardware. Open sourced since 2016, Apache-2.0, free.

Installing it is the standard framework routine: pip install the build that matches your hardware and CUDA version, then write Python. It is written mostly in C++ and Python, and it carries a large ecosystem of model libraries and end-to-end development kits on top of the core. The current line is version 3.x, actively released.

For a developer or team already committed to a framework, Paddle is worth knowing but rarely worth switching to unless you have a specific reason. Its center of gravity is China: the biggest community, the deepest tooling, and the best documentation are there, and much of it is Chinese-first. Solo researchers and teams alike will find PyTorch has the larger global ecosystem and more tutorials in English.

The catch is exactly that ecosystem gravity. Paddle is a serious, industrial-grade framework with real strengths in large-model parallelism and hardware breadth, but outside its home ecosystem you will hit more friction: fewer English answers, smaller third-party support, harder hiring for it. Pick it when you have a concrete pull toward Paddle-specific tooling or hardware, not as a default.