maderix/ANE

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

7253 stars · 960 forks observed · 2026-08-28

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

A research project demonstrating backpropagation and neural network training directly on Apple's Neural Engine using reverse-engineered private APIs (_ANEClient, _ANECompiler), bypassing Apple's inference-only CoreML restriction. It includes benchmarks documenting ANE performance characteristics and serves as a reference for direct NPU access outside CoreML.

Use cases

• train neural networks on Apple Neural Engine
• run backpropagation on ANE hardware
• benchmark Apple Neural Engine performance
• access ANE outside CoreML via private APIs
• research NPU training capabilities on Apple Silicon
• explore edge AI hardware optimization

When to choose

• you're researching direct NPU access on Apple Silicon
• you want to benchmark ANE training performance
• you need a reference for reverse-engineering Apple private ML APIs
• you're exploring edge AI compiler optimization

When to avoid

• you need a production training framework
• you want to train large models efficiently
• you need stable, maintained tooling with support
• you require high hardware utilization (currently ~5-9% of peak)
• you need a replacement for CoreML, MLX, or GPU training

Facets

library · maturity experimental

machine-learning llm-training reverse-engineering gpu-computing sdk machine-learning deep-learning hardware apple-ecosystem cpp apple-neural-engine npu backpropagation private-apis coreml proof-of-concept edge-ai research macos objective-c

Member repositories

For agents

markdown · JSON · MCP: product_card(name="maderix/ANE")