etLLM Demo App

Get hands-on with running LLMs — exported via ExecuTorch — natively on your iOS device!

LLaMa3.mp4	Phi4.mp4	Qwen3.mp4	SmolLM3.mp4
Gemma3.mp4	LLaVA.mp4	Voxtral.mp4

Requirements

Xcode 15.0 or later
A development provisioning profile with the increased-memory-limit entitlement.

Download already exported LLMs along with tokenizers from HuggingFace or export your own empowered by XNNPACK, Core ML or MPS backends.

Open the Xcode project:
```
open llm/apple/etLLM.xcodeproj
```
Click the Play button to launch the app in the Simulator.
To run on a device, ensure you have it set up for development and a provisioning profile with the increased-memory-limit entitlement. Update the app's bundle identifier to match your provisioning profile with the required capability.
After successfully launching the app, copy the exported ExecuTorch model (.pte) and tokenizer (.model, .json, .bin, etc.) files to the etLLM folder. Four models are currently supported at the moment - Gemma3, LLaMa, LLaVA, Qwen3, Phi4, SmolLM3, and Voxtral. Please ensure that your model .pte file starts with a corresponding prefix (e.g. llama, qwen3, phi4, etc.) so that the app selects the correct model type.
- For the Simulator: Drag and drop both files onto the Simulator window and save them in the On My iPhone > etLLM folder.
- For a Device: Open a separate Finder window, navigate to the Files tab, drag and drop both files into the etLLM folder, and wait for the copying to finish.
Follow the app's UI guidelines to select the model and tokenizer files from the local filesystem and issue a prompt. For more details check out the Using ExecuTorch on iOS page.