Speakr and Superwhisper are both AI meeting assistants for recording, transcription, and summaries, compared here on pricing, features, and workflow fit. Speakr: Self-hosted web app for transcribing meeting recordings with diarization, summaries, action items, per-recording chat, and library-wide semantic search. Superwhisper: Voice-to-text app for Mac, Windows, and iOS that records and transcribes meetings on-device without a bot, with speaker labels and offline processing. They overlap on ai-meeting-assistants, so the right pick depends on team size, budget, and which meeting workflows you automate.
For ai-meeting-assistants workflows, shortlist Speakr when privacy-conscious teams self-hosting transcription and summaries for internal meetings matters most, and Superwhisper when transcribing confidential zoom, teams, or meet calls without a bot matters most. Both record across Zoom, Google Meet, and Microsoft Teams; trial each on real meetings before committing.
Self-hosted web app for transcribing meeting recordings with diarization, summaries, action items, per-recording chat, and library-wide semantic search.
Configurable AI models compatible with OpenAI, OpenRouter, and local modelsCustomizable summaries plus an action-items view for decisions and tasksMulti-user support with SSO, group workspaces, and admin dashboard
Voice-to-text app for Mac, Windows, and iOS that records and transcribes meetings on-device without a bot, with speaker labels and offline processing.
Automatic speaker labels across longer recordingsAvailable on macOS, Windows, and iOSBot-free meeting recording and transcription captured from the device
Speakr is a free tier with paid upgrades (freemium); Superwhisper is a free tier with paid upgrades (freemium). Always confirm current pricing on each vendor's site before buying.
Self-hosted transcription with automatic language detection
Bot-free meeting recording and transcription captured from the device
Standout feature
Optional AI-powered speaker diarization
On-device, offline speech recognition that keeps audio local
Team usage
Customizable summaries plus an action-items view for decisions and tasks
Automatic speaker labels across longer recordings
Integrations
Per-recording chat and an Inquire Mode for semantic search across the whole library
File transcription for MP3, MP4, M4A, WAV, and WEBM formats
Languages & capture
System and browser-tab audio capture
Super Mode for dictating recaps and summaries
Best-fit workflow
Multi-user support with SSO, group workspaces, and admin dashboard
System-wide voice typing across applications
Best for
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.
Superwhisper
Choose Superwhisper if you need transcribing confidential zoom, teams, or meet calls without a bot — strengths include records meetings without adding a visible bot to the call.
Pros & cons
Speakr
+ Runs entirely on the user's own infrastructure for full data control
+ Action-item extraction and per-recording chat go beyond plain transcripts
- Current releases are alpha-stage and may not be production-stable
Superwhisper
+ Records meetings without adding a visible bot to the call
+ Offline processing keeps meeting audio off vendor servers
- Primarily a dictation tool, so meeting features are one part of a broader app
FAQ
Is Speakr or Superwhisper better for AI meeting notes?
It depends on your workflow. Speakr is strong for privacy-conscious teams self-hosting transcription and summaries for internal meetings, while Superwhisper is strong for transcribing confidential zoom, teams, or meet calls without a bot. Both transcribe and summarize meetings.
How do Speakr and Superwhisper compare on price?
Speakr is a free tier with paid upgrades and Superwhisper is a free tier with paid upgrades. Check each vendor's pricing page for the latest plans and free-tier limits.
Can I use both Speakr and Superwhisper?
Yes. Many teams run more than one meeting assistant when the workflows are complementary and the budget is justified.