Buzz: Popular open-source desktop app that transcribes and translates audio offline on your own computer using OpenAI's Whisper. Speakr: Self-hosted web app for transcribing meeting recordings with diarization, summaries, action items, per-recording chat, and library-wide semantic search. Below, they line up on price, capture method, and how each fits a real meeting stack.
How Hosiqo compares and tests toolsFinal recommendation
Shortlist Buzz when transcribing recorded meetings, interviews, podcasts, or lectures offline matters most, and Speakr when extracting action items and decisions from recorded calls matters most. Try them side by side on real calls before deciding — needs vary by team.
Popular open-source desktop app that transcribes and translates audio offline on your own computer using OpenAI's Whisper.
Self-hosted web app for transcribing meeting recordings with diarization, summaries, action items, per-recording chat, and library-wide semantic search.
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
Speakr is a self-hosted web application designed for transcribing audio recordings such as meetings, generating concise summaries and titles, and interacting with the content through a chat interface. It runs entirely on the user's own server, giving full control over data, and is dual-licensed under AGPL-3.0 and a commercial license. The project is actively maintained, with a v0.9.0-alpha release dated June 2026 and over 970 commits. Speakr produces transcripts with automatic language detection and optional AI-powered speaker diarization so users can see who said what. Its summarization can be customized with prompts, and meeting summaries include an action-items view that filters out general discussion to surface decisions, tasks, deadlines, and calendar-worthy events. For deeper interaction, a per-recording chat lets users ask questions about a single recording, while an experimental Inquire Mode provides semantic search and natural-language chat across an entire library of recordings. Speakr can capture system or browser-tab audio, supports configurable AI models and endpoints compatible with OpenAI, OpenRouter, and local models, and includes multi-user support with SSO, group workspaces, an admin dashboard, and export and sharing tools aimed at privacy-conscious teams. Pricing varies by plan. Check the official website for current pricing.
Best suited for
Buzz is a free tier with paid upgrades (freemium); Speakr is a free tier with paid upgrades (freemium). Always confirm current pricing on each vendor's site before buying.
| Feature | Buzz | Speakr |
|---|---|---|
| Core capability | Offline transcription and translation using OpenAI's Whisper | Self-hosted transcription with automatic language detection |
| Standout feature | Real-time transcription from microphone input | Optional AI-powered speaker diarization |
| Team usage | Speaker identification and speech separation for noisy audio | Customizable summaries plus an action-items view for decisions and tasks |
| Integrations | Exports to TXT, SRT, and VTT | Per-recording chat and an Inquire Mode for semantic search across the whole library |
| Languages & capture | Watch folder for automatic transcription and a command-line interface | System and browser-tab audio capture |
| Best-fit workflow | GPU acceleration via CUDA, Apple Silicon, and Vulkan | Multi-user support with SSO, group workspaces, and admin dashboard |
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.
Speakr
Choose Speakr if you need privacy-conscious teams self-hosting transcription and summaries for internal meetings — strengths include runs entirely on the user's own infrastructure for full data control.
Buzz
Speakr
It depends on your workflow. Buzz is strong for transcribing recorded meetings, interviews, podcasts, or lectures offline, while Speakr is strong for privacy-conscious teams self-hosting transcription and summaries for internal meetings. Both transcribe and summarize meetings.
Buzz is a free tier with paid upgrades and Speakr is a free tier with paid upgrades. Check each vendor's pricing page for the latest plans and free-tier limits.
Yes. Many teams run more than one meeting assistant when the workflows are complementary.
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