--- title: "whisper vs Whisperboard" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/openai-whisper-vs-saik0s-whisperboard" tools: ["openai-whisper", "saik0s-whisperboard"] --- # whisper vs Whisperboard *GraphCanon updated Sep 20, 2026* ## Verdict Pick whisper if whisper is a speech recognition model that uses large-scale weak supervision to transcribe audio to text with high accuracy; pick Whisperboard if whisperboard is an iOS app that leverages open-source technology to provide top-notch voice transcription services directly on mobile devices. [whisper](https://github.com/openai/whisper) reports 109k GitHub stars, 13k forks, and 149 open issues, last pushed Aug 31, 2026. [Whisperboard](https://github.com/Saik0s/Whisperboard) has 1.1k stars, 116 forks, and 24 open issues, last pushed Dec 18, 2025. Figures are from public GitHub metadata via [whisper's repository](https://github.com/openai/whisper) and [Whisperboard's repository](https://github.com/Saik0s/Whisperboard). | | [whisper](/tools/openai-whisper.md) | [Whisperboard](/tools/saik0s-whisperboard.md) | | --- | --- | --- | | Tagline | Robust Speech Recognition via Large-Scale Weak Supervision | An open-source iOS app for accessible quality voice transcription on mobile devices. | | Stars | 109,313 | 1,102 | | Forks | 13,251 | 116 | | Open issues | 149 | 24 | | Language | Python | Swift | | Adopt for | Whisper is a speech recognition model that uses large-scale weak supervision to transcribe audio to text with high accuracy. | Whisperboard is an iOS app that leverages open-source technology to provide top-notch voice transcription services directly on mobile devices. | | Persona | - | - | | Runtime | - | - | | License | Whisper is released under the MIT License, allowing for broad use and modification. | GPL-3.0 | | Categories | Speech & Audio | Speech & Audio | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [whisper](/tools/openai-whisper.md) | [Whisperboard](/tools/saik0s-whisperboard.md) | | --- | --- | --- | | Maintenance | Active (82%) | Slowing (36%) | | Days since push | 17d | 276d | | Open issues (now) | 149 | 24 | | Stars delta | +2.6k (30d) | +15 (30d) | | Open issues delta | +14 (30d) | 0 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/openai-whisper/trust.md) | [trust report](/tools/saik0s-whisperboard/trust.md) | ## Decision facts: whisper - **Requirements:** Whisper requires Python and specific dependencies for running the model. - **Adopt for:** Whisper is a speech recognition model that uses large-scale weak supervision to transcribe audio to text with high accuracy. - **License detail:** Whisper is released under the MIT License, allowing for broad use and modification. ## 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 whisper if… - whisper is primarily Python; Whisperboard is Swift. - License: whisper is MIT, Whisperboard is GPL-3.0. - Requirements: Whisper requires Python and specific dependencies for running the model.. - Tags unique to whisper: audio transcription, mit license, python, weak supervision. - When you need a tool that leverages large-scale weak supervision for robust speech recognition. ### Choose Whisperboard if… - Whisperboard is primarily Swift; whisper is Python. - License: Whisperboard is GPL-3.0, whisper 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 whisper - If your project requires real-time speech recognition, as Whisper may not be optimized for low-latency applications. - When you need a tool that supports a wide range of languages beyond those covered by Whisper's model. ## 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 whisper and Whisperboard? whisper: Robust Speech Recognition via Large-Scale Weak Supervision. 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 whisper over Whisperboard? Choose whisper over Whisperboard when whisper is primarily Python; Whisperboard is Swift; License: whisper is MIT, Whisperboard is GPL-3.0; Requirements: Whisper requires Python and specific dependencies for running the model.; Tags unique to whisper: audio transcription, mit license, python, weak supervision; When you need a tool that leverages large-scale weak supervision for robust speech recognition. ### When should I choose Whisperboard over whisper? Choose Whisperboard over whisper when Whisperboard is primarily Swift; whisper is Python; License: Whisperboard is GPL-3.0, whisper 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 whisper? If your project requires real-time speech recognition, as Whisper may not be optimized for low-latency applications. When you need a tool that supports a wide range of languages beyond those covered by Whisper's model. ### 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 whisper or Whisperboard more popular on GitHub? whisper has more GitHub stars (109,313 vs 1,102). Stars measure visibility, not whether either tool fits your constraints. ### Are whisper and Whisperboard open source? Yes - both are open-source projects on GitHub (whisper: MIT, Whisperboard: GPL-3.0). ### Where can I find alternatives to whisper or Whisperboard? GraphCanon lists graph-backed alternatives at [whisper alternatives](/tools/openai-whisper/alternatives) and [Whisperboard alternatives](/tools/saik0s-whisperboard/alternatives) ([whisper markdown twin](/tools/openai-whisper/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/openai-whisper-vs-saik0s-whisperboard.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, whisper or Whisperboard? whisper: 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 whisper and Whisperboard? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [whisper trust report](/tools/openai-whisper/trust); [Whisperboard trust report](/tools/saik0s-whisperboard/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=openai-whisper`](/api/graphcanon/graph?tool=openai-whisper) - 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/_