Buzz: Popular open-source desktop app that transcribes and translates audio offline on your own computer using OpenAI's Whisper. Krisp: AI noise cancellation plus meeting recording, notes and action items 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 Krisp when clear audio for remote and call-center teams 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.
AI noise cancellation plus meeting recording, notes and action items
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
Krisp removes background noise, background voices, and echo at the device level, so it works across Zoom, Google Meet, Microsoft Teams, and virtually any conferencing or calling app. Beyond noise cancellation, paid plans add unlimited AI meeting notes, transcription, recording, and accent conversion. The free plan covers 60 minutes of noise cancellation per day; AI meeting notes come with a 7-day trial and then require a paid plan.
Best suited for
Buzz is a free tier with paid upgrades (freemium); Krisp is from $8/mo (freemium). Always confirm current pricing on each vendor's site before buying.
| Feature | Buzz | Krisp |
|---|---|---|
| Core capability | Offline transcription and translation using OpenAI's Whisper | AI noise cancellation |
| Standout feature | Real-time transcription from microphone input | AI meeting notes |
| Team usage | Speaker identification and speech separation for noisy audio | Transcription |
| Integrations | Exports to TXT, SRT, and VTT | Accent conversion |
| Languages & capture | Watch folder for automatic transcription and a command-line interface | AI noise cancellation |
| Best-fit workflow | GPU acceleration via CUDA, Apple Silicon, and Vulkan | AI meeting notes |
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.
Krisp
Choose Krisp if you need removing background noise on calls — strengths include best-in-class ai noise, voice, and echo cancellation.
Buzz
Krisp
It depends on your workflow. Buzz is strong for transcribing recorded meetings, interviews, podcasts, or lectures offline, while Krisp is strong for removing background noise on calls. Both transcribe and summarize meetings.
Buzz is a free tier with paid upgrades and Krisp is from $8/mo. 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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