sbryngelson/ANEForge

Production LLM inference on the Apple Neural Engine — a practitioner's guide, complete with converters, Swift runtimes, and validated model manifests

Local AI runtime for training & running small LLMs directly on Apple Neural Engine (ANE). No CoreML. No Metal. Offline, on-device fine-tuning & inference on M-series silicon.

Training neural networks on Apple Neural Engine via reverse-engineered private APIs

Run transformers directly on Apple's Neural Engine in Swift bypass coreml entirely

Artificial Neural Engine Machine Learning Library

MLX-compatible Vulkan and ANE backends for Apple Silicon running Linux.

PMetal: high-performance Apple Silicon framework for local LLM inference, LoRA/QLoRA fine-tuning, serving, quantization, and MLX/Metal acceleration.

Everything we actually know about the Apple Neural Engine (ANE)

Inferno aims to be a super lightweight, highly efficient Rust inference engine for running open weights models on Apple Silicon with Metal, targeting machines such as a MacBook Pro with 64 GB of unified memory.