--- title: "openwhispr vs awesome-whisper" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/openwhispr-openwhispr-vs-sindresorhus-awesome-whisper" tools: ["openwhispr-openwhispr", "sindresorhus-awesome-whisper"] --- # openwhispr vs awesome-whisper *GraphCanon updated Jul 30, 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 awesome-whisper if awesome-whisper is an organized repository aggregating resources for OpenAI's Whisper AI-powered speech recognition system, covering models, apps, bindings, packages, and community tools. [openwhispr](https://openwhispr.com) reports 5.0k GitHub stars, 715 forks, and 252 open issues, last pushed Jul 30, 2026. [awesome-whisper](https://github.com/sindresorhus/awesome-whisper) has 2.4k stars, 156 forks, and 7 open issues, last pushed Mar 17, 2026. Figures are from public GitHub metadata via [openwhispr's repository](https://github.com/OpenWhispr/openwhispr) and [awesome-whisper's repository](https://github.com/sindresorhus/awesome-whisper). | | [openwhispr](/tools/openwhispr-openwhispr.md) | [awesome-whisper](/tools/sindresorhus-awesome-whisper.md) | | --- | --- | --- | | Tagline | Voice-to-text dictation app with local and cloud models | Curated resources for Whisper speech recognition system | | Stars | 5,018 | 2,361 | | Forks | 715 | 156 | | Open issues | 252 | 7 | | Language | JavaScript | - | | 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. | awesome-whisper is an organized repository aggregating resources for OpenAI's Whisper AI-powered speech recognition system, covering models, apps, bindings, packages, and community tools. | | Persona | - | - | | Runtime | - | - | | License | MIT | CC0-1.0 | | Categories | Speech & Audio | Speech & Audio | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [openwhispr](/tools/openwhispr-openwhispr.md) | [awesome-whisper](/tools/sindresorhus-awesome-whisper.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 0d | 134d | | Open issues (now) | 252 | 7 | | Owner type | Organization | User | | Full report | [trust report](/tools/openwhispr-openwhispr/trust.md) | [trust report](/tools/sindresorhus-awesome-whisper/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: awesome-whisper - **Adopt for:** awesome-whisper is an organized repository aggregating resources for OpenAI's Whisper AI-powered speech recognition system, covering models, apps, bindings, packages, and community tools. ## Choose when ### Choose openwhispr if… - License: openwhispr is MIT, awesome-whisper is CC0-1.0. - 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: anthropic, cross-platform, gemini, groq. - When you require the use of Nvidia Parakeet/Whisper models for high accuracy in a local environment without internet dependency. ### Choose awesome-whisper if… - License: awesome-whisper is CC0-1.0, openwhispr is MIT. - Tags unique to awesome-whisper: artificial-intelligence, gpt, openai, speech-to-text. - When seeking curated information on Whisper variants optimized for various platforms and languages ## 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 awesome-whisper - If looking for resources related to speech recognition systems from other providers not listed under OpenAI's Whisper ecosystem - In cases where the focus is on using pre-integrated solutions without the need for model customization ## Common questions ### What is the difference between openwhispr and awesome-whisper? openwhispr: Voice-to-text dictation app with local and cloud models. awesome-whisper: Curated resources for Whisper speech recognition system. See the comparison table for live GitHub stats and shared categories. ### When should I choose openwhispr over awesome-whisper? Choose openwhispr over awesome-whisper when License: openwhispr is MIT, awesome-whisper is CC0-1.0; 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: anthropic, cross-platform, gemini, groq; When you require the use of Nvidia Parakeet/Whisper models for high accuracy in a local environment without internet dependency. ### When should I choose awesome-whisper over openwhispr? Choose awesome-whisper over openwhispr when License: awesome-whisper is CC0-1.0, openwhispr is MIT; Tags unique to awesome-whisper: artificial-intelligence, gpt, openai, speech-to-text; When seeking curated information on Whisper variants optimized for various platforms and languages. ### 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 awesome-whisper? If looking for resources related to speech recognition systems from other providers not listed under OpenAI's Whisper ecosystem In cases where the focus is on using pre-integrated solutions without the need for model customization ### Is openwhispr or awesome-whisper more popular on GitHub? openwhispr has more GitHub stars (5,018 vs 2,361). Stars measure visibility, not whether either tool fits your constraints. ### Are openwhispr and awesome-whisper open source? Yes - both are open-source projects on GitHub (openwhispr: MIT, awesome-whisper: CC0-1.0). ### Where can I find alternatives to openwhispr or awesome-whisper? GraphCanon lists graph-backed alternatives at [openwhispr alternatives](/tools/openwhispr-openwhispr/alternatives) and [awesome-whisper alternatives](/tools/sindresorhus-awesome-whisper/alternatives) ([openwhispr markdown twin](/tools/openwhispr-openwhispr/alternatives.md), [awesome-whisper markdown twin](/tools/sindresorhus-awesome-whisper/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-sindresorhus-awesome-whisper.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, openwhispr or awesome-whisper? openwhispr: Very active. awesome-whisper: 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 awesome-whisper? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [openwhispr trust report](/tools/openwhispr-openwhispr/trust); [awesome-whisper trust report](/tools/sindresorhus-awesome-whisper/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/_