--- title: "whisper vs awesome-whisper" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/openai-whisper-vs-sindresorhus-awesome-whisper" tools: ["openai-whisper", "sindresorhus-awesome-whisper"] --- # whisper vs awesome-whisper *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 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. [whisper](https://github.com/openai/whisper) reports 109k GitHub stars, 13k forks, and 149 open issues, last pushed Aug 31, 2026. [awesome-whisper](https://github.com/sindresorhus/awesome-whisper) has 2.4k stars, 180 forks, and 7 open issues, last pushed Sep 17, 2026. Figures are from public GitHub metadata via [whisper's repository](https://github.com/openai/whisper) and [awesome-whisper's repository](https://github.com/sindresorhus/awesome-whisper). | | [whisper](/tools/openai-whisper.md) | [awesome-whisper](/tools/sindresorhus-awesome-whisper.md) | | --- | --- | --- | | Tagline | Robust Speech Recognition via Large-Scale Weak Supervision | Curated resources for Whisper speech recognition system | | Stars | 109,313 | 2,386 | | Forks | 13,251 | 180 | | Open issues | 149 | 7 | | Language | Python | - | | Adopt for | Whisper is a speech recognition model that uses large-scale weak supervision to transcribe audio to text with high accuracy. | 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 | Whisper is released under the MIT License, allowing for broad use and modification. | CC0-1.0 | | Categories | Speech & Audio | Speech & Audio | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [whisper](/tools/openai-whisper.md) | [awesome-whisper](/tools/sindresorhus-awesome-whisper.md) | | --- | --- | --- | | Maintenance | Active (82%) | Very active (96%) | | Days since push | 17d | 3d | | Open issues (now) | 149 | 7 | | Stars delta | +2.6k (30d) | +25 (30d) | | Open issues delta | +14 (30d) | 0 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/openai-whisper/trust.md) | [trust report](/tools/sindresorhus-awesome-whisper/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: 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 whisper if… - License: whisper is MIT, awesome-whisper is CC0-1.0. - Requirements: Whisper requires Python and specific dependencies for running the model.. - Tags unique to whisper: audio transcription, mit license, python, speech recognition. - When you need a tool that leverages large-scale weak supervision for robust speech recognition. ### Choose awesome-whisper if… - License: awesome-whisper is CC0-1.0, whisper is MIT. - Tags unique to awesome-whisper: ai, artificial-intelligence, gpt, openai. - When seeking curated information on Whisper variants optimized for various platforms and languages ## 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 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 whisper and awesome-whisper? whisper: Robust Speech Recognition via Large-Scale Weak Supervision. awesome-whisper: Curated resources for Whisper speech recognition system. See the comparison table for live GitHub stats and shared categories. ### When should I choose whisper over awesome-whisper? Choose whisper over awesome-whisper when License: whisper is MIT, awesome-whisper is CC0-1.0; Requirements: Whisper requires Python and specific dependencies for running the model.; Tags unique to whisper: audio transcription, mit license, python, speech recognition; When you need a tool that leverages large-scale weak supervision for robust speech recognition. ### When should I choose awesome-whisper over whisper? Choose awesome-whisper over whisper when License: awesome-whisper is CC0-1.0, whisper is MIT; Tags unique to awesome-whisper: ai, artificial-intelligence, gpt, openai; When seeking curated information on Whisper variants optimized for various platforms and languages. ### 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 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 whisper or awesome-whisper more popular on GitHub? whisper has more GitHub stars (109,313 vs 2,386). Stars measure visibility, not whether either tool fits your constraints. ### Are whisper and awesome-whisper open source? Yes - both are open-source projects on GitHub (whisper: MIT, awesome-whisper: CC0-1.0). ### Where can I find alternatives to whisper or awesome-whisper? GraphCanon lists graph-backed alternatives at [whisper alternatives](/tools/openai-whisper/alternatives) and [awesome-whisper alternatives](/tools/sindresorhus-awesome-whisper/alternatives) ([whisper markdown twin](/tools/openai-whisper/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/openai-whisper-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, whisper or awesome-whisper? whisper: Active. awesome-whisper: Very active. 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 awesome-whisper? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [whisper trust report](/tools/openai-whisper/trust); [awesome-whisper trust report](/tools/sindresorhus-awesome-whisper/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/_