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Amical vs superwhisper

Side-by-side comparison for macOS

Amical

8.0
Productivity

AI dictation app

superwhisper

7.0
Productivity

Dictation tool including LLM reformatting

Metric Amical superwhisper
Category Productivity Productivity
AI Score 8.0 7.0
30-day Installs 114 907
90-day Installs 434 2.7K
365-day Installs 771 6.7K
Version 1.2.0 2.13.2
Auto-updates Yes Yes
Deprecated No No
GitHub Stars 975 12
GitHub Forks 85 2
Open Issues 35 -
License MIT
Language TypeScript Python
Last GitHub Commit 1mo ago 1mo ago
First Seen Jan 19, 2026 Dec 13, 2024

Reviews

Amical

Amical is an AI dictation app that offers fast and accurate speech-to-text conversion, designed to be used offline with local-first functionality. It's open-source, powered by free models, and aims to enhance productivity by allowing users to type three times faster without needing a keyboard. Ideal for writers, journalists, and anyone looking for efficient text input.

Converts speech to text using AI models, working offline and locally for privacy and speed.

Pros

  • + Open-source and free to use with no hidden costs.
  • + Works offline, ensuring privacy and reliability.
  • + Fast and accurate speech-to-text conversion, claims to be 3x faster than traditional typing.

Cons

  • - Limited community discussion outside of GitHub.
  • - Requires some learning to use effectively.

superwhisper

Superwhisper is a unique dictation tool that leverages AI for offline voice-to-text conversion, offering a free alternative to premium services. It supports LLM reformatting and is designed for macOS users who need efficient text transcription and editing.

Superwhisper converts spoken words into text using AI-powered offline processing and includes features for reformatting with large language models.

Pros

  • + Free and open-source alternative to premium dictation tools
  • + AI-powered offline voice-to-text conversion
  • + Support for LLM reformatting and text editing features

Cons

  • - Unknown license status may raise concerns for some users
  • - Limited GitHub stars suggest moderate community adoption