PaddlePaddle/Paddle-Lite

Health v2 · maintenance only

Adoption not part of the score

7273 stars · 1619 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Paddle Lite is a high-performance, lightweight deep learning inference engine from Baidu's PaddlePaddle ecosystem, designed for mobile, embedded, and edge devices. It optimizes models via quantization, kernel selection, and graph fusion, and provides C++, Java, and Python APIs for on-device deployment.

Use cases

• deploy a deep learning model on Android or iOS
• run neural network inference on embedded ARM devices
• optimize and quantize a PaddlePaddle model for mobile
• run image classification or object detection on-device
• convert TensorFlow or PyTorch models for edge inference
• accelerate inference on mobile GPU or FPGA hardware

When to choose

• you need fast on-device inference on Android, iOS, or embedded Linux
• your models come from PaddlePaddle or can be converted via X2Paddle
• you need quantization and graph optimization for resource-constrained devices

When to avoid

• you need training, not inference - use full PaddlePaddle or PyTorch
• you primarily target server/cloud GPUs rather than mobile and edge
• you need broad non-Paddle model format support without conversion

Facets

library · maturity active

machine-learning deep-learning llm-inference gpu-computing deep-learning mobile-development embedded-systems machine-learning windows cpp python embedded inference-engine edge-computing model-optimization quantization on-device-ai paddlepaddle android ios linux macos arm

Member repositories

For agents

markdown · JSON · MCP: product_card(name="PaddlePaddle/Paddle-Lite")