Speech to Markdown with Local Models

Voice-to-Md.dev released Speech-to-Markdown, a 100% local app for macOS and iOS that converts voice into structured markdown documents using whisper.cpp and a local LLM, with no cloud dependency. The app offers global dictation and an agent mode with format, edit, and append capabilities.

Talk. Get clean markdown. 100% local. 🔗 voice-to-md.dev Speech-to-Markdown turns your voice into structured documents — and it ships as two apps : 🖥️ Desktop — macOS | 📱 Mobile — iOS | | |---|---|---| | Platform | macOS 13+ menu-bar app | iOS 26+, iPhone 15 Pro or newer Apple Intelligence required; Apple-Silicon iPads too | | Speech-to-text | | whisper-cpp , ffmpeg , a local LLM server none — zero setup 100% offline — nothing leaves your phoneJump to: 🖥️ Desktop app %EF%B8%8F-desktop-app-macos · 📱 Mobile app -mobile-app-ios A menu-bar app: voice → whisper.cpp → your local LLM → clean markdown. No cloud. No API keys. Nothing leaves your Mac. Everything in this part — including the dependencies and LLM-server setup below — applies to the Mac app only ; the mobile app needs none of it. ↑ This entire product spec was dictated by voice — a local LLM structured it in real time. - ⌨️ Global Dictation — Speak, and the transcript is typed straight into whatever field has focus. Terminal, browser, Slack — anything. A Spotlight-style pill shows what's happening: ⌘⌥ anywhere. - 📝 Agent Mode — live markdown editor. Speak freely; a local LLM streams your words into a clean, structured markdown document in real time. Raw transcript stays one click away. Start it from the menu bar: Everything in Agent Mode is driven from one floating, draggable capsule that hovers over the editor: Left to right: — don't wait for the auto-flush: transcribe whatever you just said and send it to the LLM✈️ Send ⌘↩ right now . Enabled while recording and idle no LLM call in flight . 🎙️ Mic — start, pause, and resume the session. Red pulse = listening. Status — Recording / Processing / Paused at a glance, with errors surfaced inline. Mode switcher and format dropdown — how your voice is applied see below and what comes out: MD default , TXT , or HTML . Each format ships its own expectations + example to the LLM, works in every mode, and the session file extension follows .md / .txt / .html — switching mid-session renames the file . Your choice is remembered across launches. 👁️ Preview — opens the session document in the default app for its type browser for HTML, your editor for markdown/plain text . 🗑️ Trash — clears the session audio, transcript, and document after a confirmation. The modes: | Mode | Icon | What it does | |---|---|---| Format default | 📄 | The whole document + your new words go to the LLM, which returns the complete restructured document. Best for free-form dictation where the model keeps improving the overall structure. | Edit | ✏️ | Your voice is an instruction, not content: "change the subtitle to Weekly Notes", "turn that list into a table". Select text in the editor first and the model treats it as the focus of the edit. | Append | ➕ | Speed mode for long documents: only the last 3 sentences + your new words are sent, and the model returns just the new content, which is appended. The LLM never re-reads the whole file, so latency stays flat as the document grows. | The flow underneath: audio is transcribed by whisper.cpp in ~4 s chunks and buffered; once ~30 words accumulate or you pause for 5 s, or hit Send , the buffer is flushed to the LLM using the prompt for the current mode and output format — and tokens stream straight into the editor. One line — installs dependencies, builds from source, and drops the app in /Applications: curl -fsSL https://raw.githubusercontent.com/xajik/voice-to-md/main/install.sh | bash Or from a checkout: git clone https://github.com/xajik/voice-to-md.git && cd voice-to-md make install deps + build + copy to /Applications …or for development: make setup && make run First launch: grant Microphone + Accessibility access, then download a Whisper model from Settings… in the menu bar Base is a great start . Signing: builds are automatically signed with your "Apple Development" identity when one is in the keychain, so re-installs keep their Microphone/Accessibility grants. No identity → ad-hoc fallback macOS will re-ask for permissions after updates . Override with make install SIGN IDENTITY="…" . Agent Mode talks to any OpenAI-compatible server. Point Speech-to-Markdown at it in Settings… default: http://127.0.0.1:8000/v1 , model auto-picked . The Whisper STT model is picked there too: Pick your server: Serve any MLX model on port 8000 — Speech-to-Markdown's default, zero config needed: brew install omlx omlx serve Qwen3.5-27B-Claude-4.6-Opus-Distilled-MLX-4bit brew install ollama ollama pull qwen3.5 or: ollama pull gemma3 ollama serve Base URL: http://127.0.0.1:11434/v1 Download from lmstudio.ai https://lmstudio.ai , grab a model, start the local server. Base URL: http://127.0.0.1:1234/v1 brew install llama.cpp llama-server -m your-model.gguf --port 8080 Base URL: http://127.0.0.1:8080/v1 | Model | Why | |---|---| Qwen3.5 27B 4-bit | Best formatting quality; the default pick | Gemma 26B 8-bit | Fast, great instruction following | Anything that follows instructions well works — Speech-to-Markdown streams tokens as they arrive, so even bigger models feel instant. Agent Mode on your phone — everything runs offline, on the device . No LLM server, no whisper install, no settings, no network. None of the desktop dependencies above apply here. Requirements:iOS 26 or lateron anApple Intelligence device — iPhone 15 Pro or newer or an Apple-Silicon iPad . Apple Intelligence must be enabled in Settings; the app shows an actionable banner if it isn't. STT : Apple's SpeechAnalyzer streams your speech to text live, fully on-device volatile text shows in gray as you talk; finalized words feed the document . LLM : Apple Foundation Models — the on-device Apple Intelligence model — formats the transcript. No server, no API keys, works in airplane mode.- Same three modes Format / Edit / Append , same MD / TXT / HTML output formats, sessions restorable from history, documents visible in the Files app. Building from source: make build-ios / make test-ios see Development %EF%B8%8F-development . Running on a device needs a development team: xcodebuild -scheme SpeechToMarkdownIOS -allowProvisioningUpdates CODE SIGN STYLE=Automatic DEVELOPMENT TEAM=<TEAMID … and Developer Mode enabled on the phone . macOS app make check verify dependencies make build release build + sign make test unit tests make generate regen .xcodeproj after editing project.yml make install build + install to /Applications make uninstall remove from /Applications iOS app make build-ios build for the iOS simulator make test-ios run the iOS test suite Both apps share one core Shared/ : transcript buffering, prompts, formats, session files. Desktop pipeline: AVAudioEngine → whisper.cpp → local LLM server. Mobile pipeline: AVAudioEngine → SpeechAnalyzer → Foundation Models. Either way, everything stays on your hardware.