Can I run an llm on iPhone
Generated on 7/30/2024
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Yes, you can run a large language model (LLM) on an iPhone. Apple provides several tools and frameworks to facilitate this process. Here are the key steps and tools involved:
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Model Preparation: You can start with any PyTorch model and convert it into the Core ML format using Core ML tools. This conversion process includes optimization techniques such as quantization and efficient key-value caching in LLMs.
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Core ML Framework: Once converted, you can run your model within your app using the Core ML framework. Core ML optimizes hardware-accelerated execution across the CPU, GPU, and neural engine, ensuring efficient performance on Apple devices.
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Apple Silicon: Apple Silicon's unified memory architecture and ML accelerators in the CPU, GPU, and neural engine provide low latency and efficient compute for machine learning workloads on device.
For more detailed information, you can refer to the following sessions from WWDC 2024:
- Explore machine learning on Apple platforms (00:00:07)
- Platforms State of the Union (00:15:45)
- Bring your machine learning and AI models to Apple silicon (00:00:59)
These sessions cover the necessary tools and workflows for running machine learning models on Apple devices, including iPhones.

Platforms State of the Union
Discover the newest advancements on Apple platforms.

Bring your machine learning and AI models to Apple silicon
Learn how to optimize your machine learning and AI models to leverage the power of Apple silicon. Review model conversion workflows to prepare your models for on-device deployment. Understand model compression techniques that are compatible with Apple silicon, and at what stages in your model deployment workflow you can apply them. We’ll also explore the tradeoffs between storage size, latency, power usage and accuracy.

Explore machine learning on Apple platforms
Get started with an overview of machine learning frameworks on Apple platforms. Whether you’re implementing your first ML model, or an ML expert, we’ll offer guidance to help you select the right framework for your app’s needs.