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Author, optimize, and deploy PyTorch models for on-device execution on Apple silicon using Core AI. Covers op compatibility rules, weight quantization/palettization for accuracy-size tradeoffs, and the full export-compile-run pipeline on Neural Engine and GPU.
npx claudepluginhub apple/coreai-models --plugin coreai-skillsEmpirical rules for authoring PyTorch models for on-device execution on Apple platforms, covering energy-efficient inference, scalable compute, and correctness testing. Use this skill whenever the user is writing, debugging, or reviewing PyTorch model code intended for on-device execution — even if they don't explicitly mention Neural Engine or Core AI. Covers BC1S layout, op compatibility, KV cache patterns, precision rules, PSNR verification, activation functions, and common issues.
Systematically explore weight compression configurations (quantization and palettization) for a PyTorch model using coreai-opt, presenting a comprehensive overview of accuracy-vs-size tradeoff options. Use this skill whenever the user wants to compress a model, explore quantization or palettization options, understand compression config tradeoffs, reduce model size, or compare different compression techniques. Also trigger when the user mentions coreai-opt compression, weight quantization exploration, or palettization exploration — even if they don't say "explore" explicitly.
Use this skill whenever the user mentions coreai-torch, TorchConverter, coreai-build, AIModel, AIProgram, .aimodel, or wants to export/compile/run a PyTorch model on Apple silicon (iPhone, iPad, Mac). Also triggers for "deploy on device", "optimize for on-device performance", onboarding new models to Core AI, or choosing between iOS and macOS deployment paths.
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Model export recipes, Python primitives, and Swift runtime utilities for building on-device AI with Core AI.
The main components include:
| Directory | What's inside |
|---|---|
models/ | Model catalog with README and export recipes. |
python/ | Python primitives for authoring and utilities for exporting models. |
swift/ | Swift package (coreai-models): runtime utilities to integrate Core AI models in your app. |
skills/ | Pluggable skills that enable coding agents to leverage Core AI more effectively. |
If you haven't installed uv, install it by
brew install uv
or
curl -LsSf https://astral.sh/uv/install.sh | sh
Once installed successfully, refer to the README.md for each model or family of models, in models folder for their exporting recipe.
macOS and iOS 27.0+
Xcode 27.0+
Core AI models are exported as standalone .aimodel files for integration into apps via the Core AI framework.
Some models require additional resources. Language models require a tokenizer, for instance, and diffusion models run multiple models in sequence as part of a single pipeline. For these cases, export recipes in this repo produce a resource folder containing one or more .aimodel files alongside any required resources. The Swift package in this repo provides runtime utilities for integrating these into an app.
Command line interface (CLI) tools are also included for running exported models directly on a Mac (requires Xcode 27.0+). See each model's README for available tools and example invocations.
Find supported models by
git clone https://github.com/apple/coreai-models.git && cd coreai-models
uv run coreai.model.registry --list-models
Run uv run coreai.model.registry --help for details.
This repo includes a plugin with skills to enable coding agents to use Core AI like an expert.
| Skill | Description |
|---|---|
working‑with‑coreai | End-to-end workflow for deploying PyTorch models on Apple silicon, covering export with coreai-torch and running with the Core AI runtime. |
model‑authoring | Empirical rules for authoring PyTorch models for on-device execution on Apple platforms, covering BC1S layout, op compatibility, KV cache patterns, precision rules, MoE, and common issues. |
model‑compression‑exploration | Systematically explore weight compression configurations (quantization and palettization) for a PyTorch model using coreai-opt. |
Installation differs depending on your coding agent of choice.
Register the marketplace:
/plugin marketplace add git@github.com:apple/coreai-models.git
Alternatively, register the marketplace from a local git checkout:
/plugin marketplace add /path/to/coreai-models
Install the plugin:
/plugin install coreai-skills@coreai-models
Register the marketplace:
codex plugin marketplace add https://github.com/apple/coreai-models
Alternatively, register the marketplace from a local git checkout:
codex plugin marketplace add /path/to/coreai-models
Install the plugin:
codex plugin add coreai-skills@coreai-models
Install the extension from a local directory:
gemini extensions install /path/to/coreai-models/skills
Once installed, the skills activate automatically based on your task context, or you can invoke them explicitly.
Core AI Models is focused on maintaining a curated, well-tested gallery of models and a reliable Swift package. We are not accepting pull requests at launch while we learn how the community uses this project.
If you open a pull request, it will be closed. This is not a reflection of the quality of your contribution but it is a deliberate scope decision for this release.
We actively want your feedback! GitHub Issues are open for: