--- title: "CosyVoice vs awesome-whisper" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/funaudiollm-cosyvoice-vs-sindresorhus-awesome-whisper" tools: ["funaudiollm-cosyvoice", "sindresorhus-awesome-whisper"] --- # CosyVoice vs awesome-whisper *GraphCanon updated Aug 23, 2026* ## Verdict Pick CosyVoice if cosyVoice is a Python-based multi-lingual large voice generation model. It supports extensive capabilities including fine-tuning, TTS (Text-To-Speech), and natural language generation; 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. [CosyVoice](https://funaudiollm.github.io/cosyvoice3) reports 23k GitHub stars, 2.6k forks, and 719 open issues, last pushed May 25, 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 [CosyVoice's repository](https://github.com/FunAudioLLM/CosyVoice) and [awesome-whisper's repository](https://github.com/sindresorhus/awesome-whisper). | | [CosyVoice](/tools/funaudiollm-cosyvoice.md) | [awesome-whisper](/tools/sindresorhus-awesome-whisper.md) | | --- | --- | --- | | Tagline | Multi-lingual large voice generation model with full-stack abilities for inference, training and deployment. | Curated resources for Whisper speech recognition system | | Stars | 22,870 | 2,361 | | Forks | 2,631 | 156 | | Open issues | 719 | 7 | | Language | Python | - | | Adopt for | CosyVoice is a Python-based multi-lingual large voice generation model. It supports extensive capabilities including fine-tuning, TTS (Text-To-Speech), and natural language generation. | 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 | Apache-2.0 | CC0-1.0 | | Categories | Inference & Serving, Model Training, Speech & Audio | Speech & Audio | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [CosyVoice](/tools/funaudiollm-cosyvoice.md) | [awesome-whisper](/tools/sindresorhus-awesome-whisper.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Slowing (36%) | | Days since push | 89d | 134d | | Open issues (now) | 719 | 7 | | Stars delta | +497 (30d) | Unknown | | Open issues delta | -37 (30d) | Unknown | | Owner type | Organization | User | | Full report | [trust report](/tools/funaudiollm-cosyvoice/trust.md) | [trust report](/tools/sindresorhus-awesome-whisper/trust.md) | ## Decision facts: CosyVoice - **Adopt for:** CosyVoice is a Python-based multi-lingual large voice generation model. It supports extensive capabilities including fine-tuning, TTS (Text-To-Speech), and natural language generation. ## 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 CosyVoice if… - License: CosyVoice is Apache-2.0, awesome-whisper is CC0-1.0. - Tags unique to CosyVoice: audio-generation, cantonese, chatbot, chatgpt. - Also covers Inference & Serving, Model Training. - When you need support for multiple languages like Cantonese, Chinese, English, Japanese, and Korean. ### Choose awesome-whisper if… - License: awesome-whisper is CC0-1.0, CosyVoice is Apache-2.0. - 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 CosyVoice - If your project specifically requires fine-tuned performance in languages not supported by CosyVoice such as Arabic or Spanish. - When strict real-time speech synthesis requirements are essential, as CosyVoice may face delays depending on the environment's computational power and model complexity. ## 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 CosyVoice and awesome-whisper? CosyVoice: Multi-lingual large voice generation model with full-stack abilities for inference, training and deployment.. awesome-whisper: Curated resources for Whisper speech recognition system. See the comparison table for live GitHub stats and shared categories. ### When should I choose CosyVoice over awesome-whisper? Choose CosyVoice over awesome-whisper when License: CosyVoice is Apache-2.0, awesome-whisper is CC0-1.0; Tags unique to CosyVoice: audio-generation, cantonese, chatbot, chatgpt; Also covers Inference & Serving, Model Training; When you need support for multiple languages like Cantonese, Chinese, English, Japanese, and Korean. ### When should I choose awesome-whisper over CosyVoice? Choose awesome-whisper over CosyVoice when License: awesome-whisper is CC0-1.0, CosyVoice is Apache-2.0; 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 CosyVoice? If your project specifically requires fine-tuned performance in languages not supported by CosyVoice such as Arabic or Spanish. When strict real-time speech synthesis requirements are essential, as CosyVoice may face delays depending on the environment's computational power and model complexity. ### 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 CosyVoice or awesome-whisper more popular on GitHub? CosyVoice has more GitHub stars (22,870 vs 2,361). Stars measure visibility, not whether either tool fits your constraints. ### Are CosyVoice and awesome-whisper open source? Yes - both are open-source projects on GitHub (CosyVoice: Apache-2.0, awesome-whisper: CC0-1.0). ### Where can I find alternatives to CosyVoice or awesome-whisper? GraphCanon lists graph-backed alternatives at [CosyVoice alternatives](/tools/funaudiollm-cosyvoice/alternatives) and [awesome-whisper alternatives](/tools/sindresorhus-awesome-whisper/alternatives) ([CosyVoice markdown twin](/tools/funaudiollm-cosyvoice/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/funaudiollm-cosyvoice-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, CosyVoice or awesome-whisper? CosyVoice: Steady. 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 CosyVoice and awesome-whisper? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [CosyVoice trust report](/tools/funaudiollm-cosyvoice/trust); [awesome-whisper trust report](/tools/sindresorhus-awesome-whisper/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=funaudiollm-cosyvoice`](/api/graphcanon/graph?tool=funaudiollm-cosyvoice) - 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/_