Tencent/FeatherCNN

Health v2 · maintenance only

Flags: no_license

Adoption not part of the score

1227 stars · 275 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

FeatherCNN is a high-performance, lightweight CNN inference library developed by Tencent, targeting ARM CPUs on mobile (iOS/Android), embedded Linux, and ARM servers. It converts Caffe models into a single binary format and packs everything into a small dependency-free code base.

Use cases

• run convolutional neural network inference on mobile devices
• deploy caffe models on android and ios
• run game AI models on phones with low latency
• embed cnn inference in embedded linux arm devices
• run neural network inference on arm servers
• minimize model runtime binary size on mobile

When to choose

• you need fast CNN inference on ARM CPUs with a tiny footprint
• you have existing Caffe models to deploy on mobile or embedded devices
• you want a dependency-free single code base for easy deployment

When to avoid

• you need GPU or non-ARM architecture support
• you need models beyond Caffe format such as ONNX or TensorFlow
• you need an actively maintained project with recent updates and support

Facets

library · maturity abandoned

machine-learning llm-inference embedded machine-learning mobile-development embedded-systems deep-learning cpp cnn-inference arm-neon caffe-models on-device-ai lightweight android ios linux arm

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For agents

markdown · JSON · MCP: product_card(name="Tencent/FeatherCNN")