Buzz: Popular open-source desktop app that transcribes and translates audio offline on your own computer using OpenAI's Whisper. WhisperLiveKit: Open-source, self-hosted real-time speech-to-text and speaker diarization toolkit with a FastAPI server and web interface, suitable for meeting transcription. The right pick comes down to team size, budget, and the workflows you want to automate.
How Hosiqo compares and tests toolsFinal recommendation
Shortlist Buzz when transcribing recorded meetings, interviews, podcasts, or lectures offline matters most, and WhisperLiveKit when building privacy-first transcription into custom applications via compatible apis matters most. Trial each on a few real meetings before you commit — the better fit usually shows fast.
Popular open-source desktop app that transcribes and translates audio offline on your own computer using OpenAI's Whisper.
Open-source, self-hosted real-time speech-to-text and speaker diarization toolkit with a FastAPI server and web interface, suitable for meeting transcription.
Buzz is a widely used open-source desktop application that transcribes and translates audio offline on the user's personal computer, powered by OpenAI's Whisper. It is MIT-licensed and actively maintained, with v1.4.4 released in March 2026, and it has grown a large community with roughly 19.7k GitHub stars. Buzz runs on macOS, Windows, and Linux, with installation options including Flatpak, Snap, and PyPI. It supports both importing existing audio and video files and real-time transcription from microphone input, and it can export results in formats such as TXT, SRT, and VTT for subtitling and documentation. The app includes an advanced transcript viewer with search and playback controls, a watch folder for automatically transcribing new files, and a command-line interface for automation. It offers GPU acceleration through CUDA for Nvidia cards, Apple Silicon support, and Vulkan for many other GPUs, which makes faster transcription practical even on laptops. Buzz also provides speaker identification and speech separation for noisy audio, plus a plugin system that adds capabilities like AI-generated summaries. Because all processing happens locally, recordings and transcripts remain on the user's machine rather than being uploaded to a cloud service. Pricing varies by plan. Check the official website for current pricing.
Best suited for
WhisperLiveKit is an open-source, self-hosted toolkit for ultra-low-latency real-time speech-to-text and speaker diarization. Rather than naively running Whisper on each audio chunk, it uses state-of-the-art simultaneous-speech research for intelligent buffering and incremental processing, which preserves transcription quality while streaming results with minimal latency. The project ships a complete backend built on FastAPI with WebSocket support, an OpenAI-compatible REST API, a Deepgram-compatible WebSocket protocol, and a simple, customizable HTML and JavaScript web interface that captures microphone audio and streams it to the server. It supports multiple ASR backends including Whisper variants, Voxtral, and Qwen3-ASR, covers 200+ languages with translation, and includes real-time speaker diarization and voice activity detection to reduce processing overhead. It can handle multiple concurrent users on a single backend and is distributed via PyPI with Docker images for both GPU and CPU. Licensed under Apache 2.0 and actively maintained into 2026, the project explicitly lists meeting transcription, accessibility tooling, and podcast or call transcription with speaker identification among its intended use cases, making it a practical building block for private, on-premise meeting transcription pipelines. Pricing varies by plan. Check the official website for current pricing.
Best suited for
Buzz is a free tier with paid upgrades (freemium); WhisperLiveKit is a free tier with paid upgrades (freemium). Always confirm current pricing on each vendor's site before buying.
| Feature | Buzz | WhisperLiveKit |
|---|---|---|
| Core capability | Offline transcription and translation using OpenAI's Whisper | Real-time streaming speech-to-text with low latency over WebSocket |
| Standout feature | Real-time transcription from microphone input | Real-time speaker diarization to distinguish multiple speakers |
| Team usage | Speaker identification and speech separation for noisy audio | FastAPI backend with OpenAI-compatible REST API and Deepgram-compatible WebSocket protocol |
| Integrations | Exports to TXT, SRT, and VTT | Multiple ASR backends (Whisper variants, Voxtral, Qwen3-ASR) and 200+ language support with translation |
| Languages & capture | Watch folder for automatic transcription and a command-line interface | Included customizable HTML/JavaScript web interface and Docker images (GPU and CPU) |
| Best-fit workflow | GPU acceleration via CUDA, Apple Silicon, and Vulkan | Voice activity detection and multi-user support on a single backend |
Buzz
Choose Buzz if you need transcribing recorded meetings, interviews, podcasts, or lectures offline — strengths include fully offline so audio and transcripts stay on the user's computer.
WhisperLiveKit
Choose WhisperLiveKit if you need self-hosted real-time meeting transcription with speaker labels — strengths include fully open source (apache 2.0) and self-hostable for private, on-premise transcription.
Buzz
WhisperLiveKit
It depends on your workflow. Buzz is strong for transcribing recorded meetings, interviews, podcasts, or lectures offline, while WhisperLiveKit is strong for self-hosted real-time meeting transcription with speaker labels. Both transcribe and summarize meetings.
Buzz is a free tier with paid upgrades and WhisperLiveKit is a free tier with paid upgrades. Check each vendor's pricing page for the latest plans and free-tier limits.
Often yes: teams combine tools when one handles capture and another handles analysis.
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