Apps
RikkaHub Agent test: Android phone agent compiles whisper.cpp on its own
XDA runs RikkaHub Agent on an Oppo Find N5 against a self-hosted Qwen 3.6 27B. The agent installed dependencies and built whisper.cpp in Termux in seven minutes.
Gemini Nano 4 ships on Samsung foldables with ML Kit Prompt API access
Google says Samsung’s new foldables carry Gemini Nano 4 with support for more than 140 languages, reachable from apps through ML Kit’s Prompt API.
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.
Apple ships Python bindings for the on-device Foundation Models framework
The apple-fm-sdk package calls the on-device Apple Intelligence model from Python on macOS 26, for scripting and batch evaluation outside Swift.
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.
ExecuTorch 1.0 reaches general availability for on-device PyTorch models
The PyTorch edge runtime promotes Core ML, Qualcomm Hexagon, Arm Ethos-U, Vulkan and XNNPACK backends to production status.
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.
Google AI Edge Gallery runs Gemma 3 1B and Qwen2.5 offline on Android
An experimental Google app downloads LiteRT models from Hugging Face, runs chat, image questions and prompt tests offline, and prints decode speed per reply.
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.
Alibaba MNN runs 4-bit LLMs on phone CPUs and GPUs, with a multimodal Android app
MNN-LLM converts PyTorch checkpoints into a 4-bit MNN format for phones, and Alibaba reports prefill 8.6 times faster than llama.cpp on an Android CPU.
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.