Paddle-Lite — High Performance Deep Learning Inference Engine for Mobile and Edge Devices

Overview

Paddle-Lite is a high-performance, lightweight, flexible, and easily extensible deep learning inference framework designed to support a variety of hardware platforms, including mobile, embedded, and edge devices. It is widely used within Baidu's internal business and has successfully supported numerous external users and enterprises in their production tasks.

Key Features

Supports multiple hardware platforms (Android, iOS, x86, macOS)
Provides model optimization tools (quantization, subgraph fusion, kernel selection)
Offers precompiled libraries for quick deployment
Supports model conversion from various frameworks (Caffe, TensorFlow, PyTorch) using X2Paddle
Provides C++, Java, and Python APIs with comprehensive usage examples

Use Cases

Mobile and edge device applications requiring high-performance deep learning inference
Enterprises and developers looking to deploy PaddlePaddle models on various devices
Model optimization and acceleration for resource-constrained environments

Advantages

High performance and low resource consumption
Easy model conversion and optimization
Extensive support for different hardware platforms
Comprehensive documentation and community support

Limitations / Considerations

May require additional setup for non-standard hardware or operating systems
Some features may be more suitable for specific hardware platforms

TensorFlow Lite: A lightweight deep learning framework for mobile and embedded devices, with a focus on Android and iOS. TensorFlow Lite has a broader range of supported devices but may not be as optimized for Chinese markets.
ONNX Runtime: An open-source scoring engine for Open Neural Network Exchange (ONNX) models, supporting various hardware platforms. ONNX Runtime is more focused on model interchangeability across different frameworks.
OpenVINO Toolkit: An open-source toolkit from Intel for optimizing and deploying deep learning models on Intel hardware. It is more specialized for Intel platforms but offers advanced optimization features.

Basic Information

GitHub: https://github.com/PaddlePaddle/Paddle-Lite
Stars: 7,181
License: Apache 2.0
Last Commit: 2025-11-15

📊 Project Information

Project Name: Paddle-Lite
GitHub URL: https://github.com/PaddlePaddle/Paddle-Lite
Programming Language: C++
⭐ Stars: 7,181
🍴 Forks: 1,627
📅 Created: 2017-09-20
🔄 Last Updated: 2025-11-15

🏷️ Project Topics

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🎮 Online Demos

📚 Documentation

This article is automatically generated by AI based on GitHub project information and README content analysis

Paddle-Lite

Project Description