Lekh AI
Private, offline AI for iPhone, and iPad
What it does
Lekh AI is a native iPhone, iPad, and Mac app that runs powerful AI entirely on‑device. No cloud APIs, no subscriptions, and no data leaving your phone. It combines LLM chat, vision, PDF/document analysis, image generation, and voice in one offline assistant. Chat with models like Gemma, Qwen, Llama, Phi, Mistral, OpenELM Voice chat with Kokoro TTS No subscriptions. One‑time $2. 100% private. If you’re curious about what on‑device AI can do in 2026, this is it. 🚀
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Lekh AI – Local AI Studio for macOSMar 2026 · apps.apple.com · ▲1Run AI models, images, and TTS locally on your Mac
- SOSwiftAI – open-source library to easily build LLM features on iOS/macOS2025 · github.com · ▲74
We built SwiftAI, an open-source Swift library that lets you use Apple’s on-device LLMs when available (Apple opened access in June), and fall back to a cloud model when they aren’t available — all without duplicating code. SwiftAI gives you: - A single, model-agnostic API - An agent/tool loop - Strongly-typed structured outputs - Optional chat state Backstory: We started experimenting with Apple’s local models because they’re free (no API calls), private, and work offline. The problem: not all devices support them (older iPhones, Apple Intelligence disabled, low battery, etc.). That…
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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
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Hey HN! I wanted to share something I built over the last few weeks: isometric.nyc is a massive isometric pixel art map of NYC, built with nano banana and coding agents. I didn't write a single line of code. Of course no-code doesn't mean no-engineering. This project took a lot more manual labor than I'd hoped! I wrote a deep dive on the workflow and some thoughts about the future of AI coding and creativity: http://cannoneyed.com/projects/isometric-nyc
AI · Jan 2026 · cannoneyed.com
Automatic AI-powered code reviews the moment you open a PR
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