paddlepaddle
Parallel Distributed Deep Learning
Decision gist · record as of 2026-08-14
Yes, if you are building or deploying deep learning models and want an actively maintained framework with strong industrial backing and cross-platform support. The permissive Apache-2.0 license, stable production status, and zero known vulnerabilities support adoption. Medium install friction is typical for ML frameworks and not a barrier. Best suited for teams already familiar with deep learning frameworks or those targeting the framework's specific strengths in distributed training and edge deployment.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- GPU version requires separate installation; CPU version installs via standard pip.
- Python 3.9–3.13 supported on Windows, Linux, macOS (CPU only on macOS).
- Medium install friction due to platform-specific wheels for Python 3.9–3.13 across macOS ARM64, Linux x86_64, and Windows.
License · maintenance · safety
Apache Software License (permissive) — Apache-2.0 permissive license allows commercial and private use with minimal restrictions; you must include a copy of the license and state significant changes, but no copyleft obligations apply to your own code.
last release 2026-03-24 (143 days) · last repo commit 2026-08-14 · 24,050 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 2,415,720 downloads/mo, #3,075 on PyPI
Alternatives
Verify before relying
pip install paddlepaddle
import paddlepaddle- Whether the 2.3 million developers claim and industrial adoption scope remain current as of version 3.3.1.
- Performance characteristics and inference speed improvements on specific hardware relative to other frameworks.
- Completeness and maintenance status of the 100+ mainstream models and 200+ pre-training models mentioned.
What it is and what it does
PaddlePaddle is an open-source deep learning framework designed for both research and industrial deployment. It supports declarative and imperative programming styles, allowing developers to build neural networks flexibly while maintaining high runtime performance. The framework includes pre-built models, training utilities, and inference acceleration tools, with particular focus on distributed training at scale and cross-platform deployment from cloud servers to edge devices.
The package depends on numpy for tensor operations, protobuf for serialization, Pillow for image handling, httpx, opt_einsum, networkx, typing_extensions, safetensors, and setuptools. It is actively maintained and classified as production-stable. Installation is straightforward via pip, though platform-specific wheels are required and GPU support needs a separate variant. The framework is licensed under Apache-2.0, making it suitable for both open and commercial projects.
Use it for
- Train large-scale neural networks on distributed clusters using the framework's distributed training infrastructure.
- Deploy trained models to edge devices and mobile platforms using inference acceleration tools.
- Prototype and experiment with deep learning models using pre-built mainstream models from the framework's library.
- Build computer vision applications leveraging Pillow integration and pre-trained vision models.
- Develop natural language processing systems using the framework's NLP model collections and utilities.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are building or deploying deep learning models and want an actively maintained framework with strong industrial backing and cross-platform support.
The permissive Apache-2.0 license, stable production status, and zero known vulnerabilities support adoption. Medium install friction is typical for ML frameworks and not a barrier. Best suited for teams already familiar with deep learning frameworks or those targeting the framework's specific strengths in distributed training and edge deployment.
Install
paddlepaddle on PyPI
Before you install
Medium install friction due to platform-specific wheels for Python 3.9–3.13 across macOS ARM64, Linux x86_64, and Windows. Nine runtime dependencies including numpy, protobuf, and Pillow add weight. Active maintenance with recent commits and stable production status mitigate friction.
GPU version requires separate installation; CPU version installs via standard pip. Python 3.9–3.13 supported on Windows, Linux, macOS (CPU only on macOS).
License in practice
Apache-2.0 permissive license allows commercial and private use with minimal restrictions; you must include a copy of the license and state significant changes, but no copyleft obligations apply to your own code.
Quickstart
pip install paddlepaddle
import paddlepaddleVerify before relying
- Whether the 2.3 million developers claim and industrial adoption scope remain current as of version 3.3.1.
- Performance characteristics and inference speed improvements on specific hardware relative to other frameworks.
- Completeness and maintenance status of the 100+ mainstream models and 200+ pre-training models mentioned.
Package facts
| License | Apache Software License permissive |
| Python support | Not specified |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | 9 packageshttpxnumpyprotobufPillowopt_einsumnetworkxtyping_extensionssafetensorssetuptools |
| Maintenance | Actively maintained 143 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 2,415,720 / month, #3,075 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersIntended Audience :: EducationIntended Audience :: Science/ResearchLicense :: OSI Approved :: Apache Software LicenseOperating System :: OS IndependentProgramming Language :: C++Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.9Typing :: Typed |
Evidence: paddlepaddle-3.3.1-cp310-cp310-macosx_11_0_arm64.whl; paddlepaddle-3.3.1-cp310-cp310-manylinux1_x86_64.whl; paddlepaddle-3.3.1-cp310-cp310-win_amd64.whl; paddlepaddle-3.3.1-cp311-cp311-macosx_11_0_arm64.whl; paddlepaddle-3.3.1-cp311-cp311-manylinux1_x86_64.whl; paddlepaddle-3.3.1-cp311-cp311-win_amd64.whl; paddlepaddle-3.3.1-cp312-cp312-macosx_11_0_arm64.whl; paddlepaddle-3.3.1-cp312-cp312-manylinux1_x86_64.whl; paddlepaddle-3.3.1-cp312-cp312-win_amd64.whl; paddlepaddle-3.3.1-cp313-cp313-macosx_11_0_arm64.whl; paddlepaddle-3.3.1-cp313-cp313-manylinux1_x86_64.whl; paddlepaddle-3.3.1-cp313-cp313-win_amd64.whl; paddlepaddle-3.3.1-cp39-cp39-macosx_11_0_arm64.whl; paddlepaddle-3.3.1-cp39-cp39-manylinux1_x86_64.whl; paddlepaddle-3.3.1-cp39-cp39-win_amd64.whl
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