iOS
16 updates on iOS.
Airgap is a React Native kit for support chatbots that answer offline
Xavier Puspus published a React Native kit for support chatbots that answer without a network, running a 2.4 GB Gemma 4 E2B file through llama.rn.
Show HN: Off Grid runs text, image, vision and speech models offline on phones
An MIT-licensed Android and iOS app bundles llama.cpp, Stable Diffusion and Whisper for offline use. The Show HN thread reached 124 points and 66 comments.
Apple opens its on-device model to all apps with the Foundation Models framework
Any app can call the roughly 3-billion-parameter on-device model from Swift, offline and free of charge, with guided generation and tool calling.
Locally AI runs Llama, Gemma and Qwen offline on iPhone and iPad through MLX
Adrien Grondin shipped a free iPhone and iPad app that downloads open-weight models and runs them on device, built on Apple silicon through MLX.
HuggingSnap describes what the iPhone camera sees with a 500M model on the phone
Hugging Face released an iPhone app that runs SmolVLM2 at 500M parameters through MLX, describing camera scenes, photos and video with no cloud call.
Meta ships Llama Stack with Swift and Kotlin clients for on-device inference
Meta standardised its Llama APIs so mobile apps can swap a cloud endpoint for an on-device ExecuTorch runtime without changing the calling code.
Ai2 releases OLMoE, 7B parameters with 1B active per token
Ai2's mixture-of-experts model holds 6.9B parameters but runs 1.3B per token, and its iOS app runs it offline on an iPhone 15 Pro or newer.
torchchat runs Llama 3 8B on a Galaxy S23 and iPhone at more than 8 tok/s
PyTorch's demonstration codebase exports Llama models to ExecuTorch and ships iOS and Android sample apps for running them on a phone.
Apple Intelligence pairs a 3-billion-parameter on-device model with a server model
Apple reports 0.6 ms per prompt token and 30 tokens per second on an iPhone 15 Pro for a model compressed to an average of 3.7 bits per weight.
Google ships an experimental MediaPipe LLM Inference API for web, Android and iOS
The experimental API runs Gemma 2B, Phi 2, Falcon 1B and Stable LM 3B fully on device, with int8 and int4 weights.
Apple publishes MLX, where CPU and GPU share arrays without copies
Apple machine learning research released an array framework for Apple silicon with a unified memory model, lazy evaluation and Swift bindings for iOS.
LLM.swift wraps llama.cpp for on-device text generation in Swift apps
A Swift package that wraps llama.cpp so iOS, macOS, watchOS, tvOS and visionOS apps can load a GGUF file and generate text on the device.