ANEForge: Python for direct computation on the Apple Neural Engine

📰 ArXiv cs.AI

Learn how to use ANEForge, a Python package for direct computation on the Apple Neural Engine, and unlock its potential for AI acceleration

advanced Published 17 Jun 2026

Action Steps

Install ANEForge using pip
Build a lazy tensor graph using ANEForge's 58 fused operators
Compile the graph to run directly on the Apple Neural Engine
Test and optimize your model's performance using ANEForge
Compare the performance of your model on the ANE versus CPU or GPU

Who Needs to Know This

AI engineers and researchers working with Apple devices can benefit from using ANEForge to optimize their models' performance and leverage the Apple Neural Engine's capabilities

Key Insight

💡 ANEForge allows direct access to the Apple Neural Engine, bypassing CoreML and enabling more control over AI model execution

Full Article

Title: ANEForge: Python for direct computation on the Apple Neural Engine

Abstract:
arXiv:2606.17090v1 Announce Type: cross Abstract: ANEForge is a Python package that programs the Apple Neural Engine (ANE), the fixed-function neural accelerator on every recent Apple device, directly and without CoreML. In production the engine is reachable only through CoreML, which treats it as a scheduling option: no configuration requires the ANE, and a model can silently run on the CPU or GPU instead. ANEForge compiles a lazy tensor graph, built from 58 fused operators and 19 native bridge

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