No. 15 of 36 ·Deep Learning Software

PaddlePaddle

Windows · Mac · Linux · Self-hosted · API

Freedom report

Two barsScore 5.6

Free tierNo free tier on record
Open codeNo open-source code on record
Runs widely3 of 6 device platforms
DocumentedPlans, terms and facts published

PaddlePaddle is ranked #15 of 36 in deep learning software on Freedom251. It runs on API, Linux, macOS, Self-hosted, Windows.

Compared on deep learning software

Free plan: Yes
Training mode: local
Deployment targets: multiple
GPU acceleration: Yes
Distributed training: Yes
Supported languages: Python

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The record

Purpose: PaddlePaddle describes itself as an efficient, flexible, extensible deep learning framework intended to make deep learning innovation and application easier.
Training and inference: Its APIs cover tensor operations, neural networks, optimizers, model training, and inference.
Graph modes: The framework supports dynamic graphs and static graphs, including APIs to convert dynamic graphs to static graphs.
Mixed precision: Its automatic mixed precision API can select FP16 or FP32 for different operators during training.
Integrations: Paddle Inference documents integrations with TensorRT, cuDNN, oneDNN, and Paddle Lite.
Installation: The installation guide offers pip installation for Linux, macOS, and Windows, with CPU and GPU versions where supported.
Self hosting: The framework can be compiled from source on Linux, and its documentation recommends Docker as a simpler compilation environment.
Hardware requirements: The Linux source build guide specifies 64-bit Linux and Python 3.9 through 3.13, and recommends NVIDIA GPU support when the listed CUDA and hardware conditions are met.
Limits: The Windows source build guide says distributed training and NCCL are not supported on Windows and its GPU build supports only one GPU.
Intended users: The documentation recommends pip installation for users who only need to use PaddlePaddle and source compilation for developers who need to develop the framework.
Maker: The project’s official GitHub repository identifies PaddlePaddle as its core framework; Baidu’s investor FAQ lists its headquarters as Beijing and says it was incorporated in 2000.
Product: PaddlePaddle is an efficient, flexible, and extensible deep learning framework.
Model development: Its guides cover model development and additional uses for model development.
Inference and deployment: The guides describe using trained models for inference and deployment.

Where it ranks on Freedom251

Best Deep Learning Software in 2026#15 of 36

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Sources

paddlepaddle.org.cn/documentation/docs/en/api/index_en.html· checked 3 Oct 2026
paddlepaddle.org.cn/documentation/docs/en/guides/performanc· checked 3 Oct 2026
paddlepaddle.org.cn/lite/v2.11/guides/install/requirements.· checked 3 Oct 2026
paddlepaddle.org.cn/documentation/docs/en/install/pip/fromp· checked 3 Oct 2026
paddlepaddle.org.cn/documentation/docs/en/install/compile/l· checked 3 Oct 2026
paddlepaddle.org.cn/documentation/docs/en/3.0/install/compi· checked 3 Oct 2026
paddlepaddle.org.cn/documentation/docs/en/2.4/install/index· checked 3 Oct 2026
github.com/PaddlePaddle/Paddle· checked 3 Oct 2026
paddlepaddle.org.cn/documentation/docs/en/guides/index_en.h· checked 4 Oct 2026
paddlepaddle.org.cn/documentation/docs/en/install/index_en.· checked 4 Oct 2026
paddlepaddle.org.cn/documentation/docs/zh/install/Tables_en· checked 4 Oct 2026
paddlepaddle.org.cn/en· checked 4 Oct 2026