Vibe is an open-source desktop application for transcribing audio and video entirely on your own device. Built in Rust and released under the MIT license, it wraps state-of-the-art speech recognition models behind a friendly cross-platform GUI, so users can turn recordings into text without sending anything to the cloud. Past 6,700 GitHub stars and updated almost daily, Vibe has become a popular privacy-first alternative to hosted transcription services for journalists, researchers, and anyone who works with sensitive recordings. ## Fully Offline, Privacy-First Transcription The core promise is that no data ever leaves your machine. Vibe runs the entire transcription pipeline locally, which makes it a fit for confidential interviews, medical or legal audio, and any workflow where uploading files to a third party is unacceptable. It transcribes almost every language, can translate any language to English, and supports speaker diarization to label who said what. Because it is a native desktop app rather than a web service, it works without an internet connection once models are downloaded. ## Broad Model and Format Support Under the hood Vibe supports Whisper along with newer engines including NVIDIA Parakeet TDT v3 and Nemotron 3.5, and it lets advanced users pass model arguments or integrate custom models from their own site via a `vibe://` download link. Output is equally flexible: transcripts can be exported as SRT, VTT, TXT, HTML, PDF, JSON, or DOCX, with a stable-timestamps mode that produces subtitle- and movie-grade timing backed by voice activity detection. Users can batch-transcribe many files at once, preview results in real time, and even pull audio directly from popular sites like YouTube, Vimeo, and others. ## Optimized for Real Hardware Vibe is engineered to make good use of whatever machine it runs on. It is optimized for GPUs across macOS, Windows, and Linux, with acceleration paths for NVIDIA, AMD, and Intel hardware through Vulkan and CoreML. Beyond file transcription, it can capture system audio and microphone input, print transcripts directly to a printer, and expose an HTTP API with Swagger docs plus a command-line interface for scripting and automation. Automatic updates keep the app current without manual reinstalls. ## AI Analysis Built In Transcription is only half the workflow, so Vibe adds summarization on top. It can produce quick, multilingual summaries of transcripts using the Claude API, or run fully local AI analysis and batch summaries through Ollama for users who want to keep even the summarization step offline. Combined with caption-length presets tuned for videos and reels, this turns Vibe from a raw transcriber into a lightweight end-to-end tool for turning recordings into usable notes, subtitles, and summaries. ## Trade-offs and Limitations As a local-first app, transcription speed and quality depend heavily on your hardware and the model you choose — large Whisper models are accurate but slow on CPU-only machines, while stable-timestamps mode trades speed for timing precision. Mobile support for iOS and Android is still listed as coming soon, so the tool is desktop-only for now. Some advanced features, like custom model arguments, assume familiarity with the underlying speech models, and the summarization feature's cloud option relies on an external Claude API key unless you opt for the local Ollama path. ## Who Should Use This Vibe is a strong choice for anyone who needs accurate, private transcription without a subscription: journalists handling confidential sources, researchers processing interview audio, content creators generating subtitles, and developers who want a scriptable local transcription backend via its CLI and HTTP API. The MIT license, active development, and broad model and format support make it one of the most capable open-source desktop transcription tools available today.