--- title: "openwhispr vs Whisperboard" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/openwhispr-openwhispr-vs-saik0s-whisperboard" tools: ["openwhispr-openwhispr", "saik0s-whisperboard"] --- # openwhispr vs Whisperboard *GraphCanon updated Jul 31, 2026* ## Verdict Pick openwhispr if openWhispr is an open-source voice-to-text dictation application that features both local and cloud-based models, emphasizing privacy and cross-platform compatibility; pick Whisperboard if whisperboard is an iOS app that leverages open-source technology to provide top-notch voice transcription services directly on mobile devices. [openwhispr](https://openwhispr.com) reports 5.0k GitHub stars, 715 forks, and 252 open issues, last pushed Jul 30, 2026. [Whisperboard](https://github.com/Saik0s/Whisperboard) has 1.1k stars, 111 forks, and 24 open issues, last pushed Dec 18, 2025. Figures are from public GitHub metadata via [openwhispr's repository](https://github.com/OpenWhispr/openwhispr) and [Whisperboard's repository](https://github.com/Saik0s/Whisperboard). | | [openwhispr](/tools/openwhispr-openwhispr.md) | [Whisperboard](/tools/saik0s-whisperboard.md) | | --- | --- | --- | | Tagline | Voice-to-text dictation app with local and cloud models | An open-source iOS app for accessible quality voice transcription on mobile devices. | | Stars | 5,018 | 1,087 | | Forks | 715 | 111 | | Open issues | 252 | 24 | | Language | JavaScript | Swift | | Adopt for | OpenWhispr is an open-source voice-to-text dictation application that features both local and cloud-based models, emphasizing privacy and cross-platform compatibility. | Whisperboard is an iOS app that leverages open-source technology to provide top-notch voice transcription services directly on mobile devices. | | Persona | - | - | | Runtime | - | - | | License | MIT | GPL-3.0 | | Categories | Speech & Audio | Speech & Audio | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [openwhispr](/tools/openwhispr-openwhispr.md) | [Whisperboard](/tools/saik0s-whisperboard.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 0d | 224d | | Open issues (now) | 252 | 24 | | Owner type | Organization | User | | Full report | [trust report](/tools/openwhispr-openwhispr/trust.md) | [trust report](/tools/saik0s-whisperboard/trust.md) | ## Decision facts: openwhispr - **Requirements:** Min 4 GB RAM; Development and runtime environment requires Node.js version 24+.; Support for Nvidia Parakeet/Whisper models may require additional setup specific to the hardware and software configurations. - **Adopt for:** OpenWhispr is an open-source voice-to-text dictation application that features both local and cloud-based models, emphasizing privacy and cross-platform compatibility. ## Decision facts: Whisperboard - **Adopt for:** Whisperboard is an iOS app that leverages open-source technology to provide top-notch voice transcription services directly on mobile devices. ## Choose when ### Choose openwhispr if… - openwhispr is primarily JavaScript; Whisperboard is Swift. - License: openwhispr is MIT, Whisperboard is GPL-3.0. - Requirements: Min 4 GB RAM; Development and runtime environment requires Node.js version 24+.; Support for Nvidia Parakeet/Whisper models may require additional setup specific to the hardware and software configurations.. - Tags unique to openwhispr: ai, anthropic, cross-platform, gemini. - When you require the use of Nvidia Parakeet/Whisper models for high accuracy in a local environment without internet dependency. ### Choose Whisperboard if… - Whisperboard is primarily Swift; openwhispr is JavaScript. - License: Whisperboard is GPL-3.0, openwhispr is MIT. - Tags unique to Whisperboard: audio-to-text, composable-architecture, ios, openai. - When you require precise and reliable speech-to-text functionality on iOS devices, as Whisperboard specifically targets quality in its transcription process across these platforms. ## When NOT to use openwhispr - When you have limited computational power on your device and rely heavily on cloud resources for processing voice-to-text without the overhead of managing local machine learning models. - If your application must work on platforms that are not supported by OpenWhispr, such as mobile devices or specialized operating systems. ## When NOT to use Whisperboard - Avoid if you need compatibility with Android devices as Whisperboard focuses solely on iOS functionality and user experience. - Consider other options if the project demands real-time transcription capabilities that go beyond Whisperboard's current scope in its implementation and feature set. ## Common questions ### What is the difference between openwhispr and Whisperboard? openwhispr: Voice-to-text dictation app with local and cloud models. Whisperboard: An open-source iOS app for accessible quality voice transcription on mobile devices.. See the comparison table for live GitHub stats and shared categories. ### When should I choose openwhispr over Whisperboard? Choose openwhispr over Whisperboard when openwhispr is primarily JavaScript; Whisperboard is Swift; License: openwhispr is MIT, Whisperboard is GPL-3.0; Requirements: Min 4 GB RAM; Development and runtime environment requires Node.js version 24+.; Support for Nvidia Parakeet/Whisper models may require additional setup specific to the hardware and software configurations.; Tags unique to openwhispr: ai, anthropic, cross-platform, gemini; When you require the use of Nvidia Parakeet/Whisper models for high accuracy in a local environment without internet dependency. ### When should I choose Whisperboard over openwhispr? Choose Whisperboard over openwhispr when Whisperboard is primarily Swift; openwhispr is JavaScript; License: Whisperboard is GPL-3.0, openwhispr is MIT; Tags unique to Whisperboard: audio-to-text, composable-architecture, ios, openai; When you require precise and reliable speech-to-text functionality on iOS devices, as Whisperboard specifically targets quality in its transcription process across these platforms. ### When should I avoid openwhispr? When you have limited computational power on your device and rely heavily on cloud resources for processing voice-to-text without the overhead of managing local machine learning models. If your application must work on platforms that are not supported by OpenWhispr, such as mobile devices or specialized operating systems. ### When should I avoid Whisperboard? Avoid if you need compatibility with Android devices as Whisperboard focuses solely on iOS functionality and user experience. Consider other options if the project demands real-time transcription capabilities that go beyond Whisperboard's current scope in its implementation and feature set. ### Is openwhispr or Whisperboard more popular on GitHub? openwhispr has more GitHub stars (5,018 vs 1,087). Stars measure visibility, not whether either tool fits your constraints. ### Are openwhispr and Whisperboard open source? Yes - both are open-source projects on GitHub (openwhispr: MIT, Whisperboard: GPL-3.0). ### Where can I find alternatives to openwhispr or Whisperboard? GraphCanon lists graph-backed alternatives at [openwhispr alternatives](/tools/openwhispr-openwhispr/alternatives) and [Whisperboard alternatives](/tools/saik0s-whisperboard/alternatives) ([openwhispr markdown twin](/tools/openwhispr-openwhispr/alternatives.md), [Whisperboard markdown twin](/tools/saik0s-whisperboard/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/openwhispr-openwhispr-vs-saik0s-whisperboard.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, openwhispr or Whisperboard? openwhispr: Very active. Whisperboard: Slowing. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for openwhispr and Whisperboard? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [openwhispr trust report](/tools/openwhispr-openwhispr/trust); [Whisperboard trust report](/tools/saik0s-whisperboard/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=openwhispr-openwhispr`](/api/graphcanon/graph?tool=openwhispr-openwhispr) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_