Buzz: Popular open-source desktop app that transcribes and translates audio offline on your own computer using OpenAI's Whisper. OpenTranscribe: Self-hosted, containerized web app for transcribing and analyzing audio/video with WhisperX, speaker diarization, search, and collaboration. We compare them on cost, capture approach, and day-to-day fit so you can choose faster.
How Hosiqo compares and tests toolsFinal recommendation
Shortlist Buzz when transcribing recorded meetings, interviews, podcasts, or lectures offline matters most, and OpenTranscribe when collaborative review of transcripts with time-stamped annotations matters most. Test each on your own meetings; the right choice tends to become obvious quickly.
Popular open-source desktop app that transcribes and translates audio offline on your own computer using OpenAI's Whisper.
Self-hosted, containerized web app for transcribing and analyzing audio/video with WhisperX, speaker diarization, search, and collaboration.
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
OpenTranscribe is a self-hosted, containerized web application for transcribing and analyzing audio and video files using current AI models. It is built with a FastAPI backend, a Svelte/TypeScript progressive web app frontend, and a Docker-based stack that includes PostgreSQL, Redis/Celery task queues, MinIO object storage, and OpenSearch for full-text indexing. Transcription is handled by WhisperX with the large-v3-turbo model and Faster-Whisper, supporting more than 100 languages, while automatic speaker diarization uses PyAnnote v4 with overlap detection. The project is licensed under AGPL-3.0 and is actively maintained, with v0.4.1 released in April 2026. Beyond transcription, OpenTranscribe provides AI-powered summarization (including BLUF-format and custom JSON schemas), topic extraction, and content analysis through multiple LLM providers such as OpenAI, Claude, vLLM, Ollama, and OpenRouter. Collaboration features include time-stamped comments and annotations, and the platform can automatically import media from local folders, S3, and SMB shares. It also supports a set of cloud ASR providers as alternatives to local transcription, giving teams flexibility between fully local processing and managed services while keeping the application running on their own infrastructure. Pricing varies by plan. Check the official website for current pricing.
Best suited for
Buzz is a free tier with paid upgrades (freemium); OpenTranscribe is a free tier with paid upgrades (freemium). Always confirm current pricing on each vendor's site before buying.
| Feature | Buzz | OpenTranscribe |
|---|---|---|
| Core capability | Offline transcription and translation using OpenAI's Whisper | WhisperX transcription with large-v3-turbo and 100+ language support |
| Standout feature | Real-time transcription from microphone input | Automatic speaker diarization via PyAnnote v4 with overlap detection |
| Team usage | Speaker identification and speech separation for noisy audio | Full-text search and filtering powered by OpenSearch |
| Integrations | Exports to TXT, SRT, and VTT | AI summarization, topic extraction, and content analysis via multiple LLM providers |
| Languages & capture | Watch folder for automatic transcription and a command-line interface | Time-stamped comments for collaboration and annotation |
| Best-fit workflow | GPU acceleration via CUDA, Apple Silicon, and Vulkan | Auto-import from local folders, S3, and SMB shares |
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.
OpenTranscribe
Choose OpenTranscribe if you need teams self-hosting a searchable archive of transcribed meeting and media recordings — strengths include fully self-hosted web app with a complete transcription-and-analysis stack.
Buzz
OpenTranscribe
It depends on your workflow. Buzz is strong for transcribing recorded meetings, interviews, podcasts, or lectures offline, while OpenTranscribe is strong for teams self-hosting a searchable archive of transcribed meeting and media recordings. Both transcribe and summarize meetings.
Buzz is a free tier with paid upgrades and OpenTranscribe 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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