--- title: "ChatTTS vs Matcha-TTS" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/2noise-chattts-vs-shivammehta25-matcha-tts" tools: ["2noise-chattts", "shivammehta25-matcha-tts"] --- # ChatTTS vs Matcha-TTS *GraphCanon updated Aug 16, 2026* ## Verdict Pick ChatTTS if chatTTS is a Python-based repository for generating speech tailored to everyday conversations in both Chinese and English; pick Matcha-TTS if matcha-TTS employs non-autoregressive probabilistic techniques with deep learning for fast TTS generation. [ChatTTS](https://2noise.com) reports 40k GitHub stars, 4.3k forks, and 60 open issues, last pushed Apr 10, 2026. [Matcha-TTS](https://shivammehta25.github.io/Matcha-TTS/) has 1.3k stars, 213 forks, and 35 open issues, last pushed Jul 13, 2026. Figures are from public GitHub metadata via [ChatTTS's repository](https://github.com/2noise/ChatTTS) and [Matcha-TTS's repository](https://github.com/shivammehta25/Matcha-TTS). | | [ChatTTS](/tools/2noise-chattts.md) | [Matcha-TTS](/tools/shivammehta25-matcha-tts.md) | | --- | --- | --- | | Tagline | A generative speech model for daily dialogue | Matcha-TTS is a fast TTS architecture with conditional flow matching | | Stars | 39,768 | 1,339 | | Forks | 4,257 | 213 | | Open issues | 60 | 35 | | Language | Python | Jupyter Notebook | | Adopt for | ChatTTS is a Python-based repository for generating speech tailored to everyday conversations in both Chinese and English. | Matcha-TTS employs non-autoregressive probabilistic techniques with deep learning for fast TTS generation. | | Persona | - | - | | Runtime | - | - | | License | Licensed under AGPL-3.0, which allows for free use, distribution, and modification as long as these rights are maintained in derivative works. | MIT | | Categories | AI Agents, Speech & Audio | Speech & Audio | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ChatTTS](/tools/2noise-chattts.md) | [Matcha-TTS](/tools/shivammehta25-matcha-tts.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Active (82%) | | Days since push | 127d | 16d | | Open issues (now) | 60 | 35 | | Stars delta | +140 (30d) | Unknown | | Open issues delta | -1 (30d) | Unknown | | Owner type | Organization | User | | Full report | [trust report](/tools/2noise-chattts/trust.md) | [trust report](/tools/shivammehta25-matcha-tts/trust.md) | ## Shared compatibility - **Python**: [ChatTTS](/tools/2noise-chattts.md) - Python runtime; [Matcha-TTS](/tools/shivammehta25-matcha-tts.md) - Python runtime ## Decision facts: ChatTTS - **Hosting:** unknown - **Requirements:** Python-based implementation means that familiarity with Python is necessary for effective use. - **Adopt for:** ChatTTS is a Python-based repository for generating speech tailored to everyday conversations in both Chinese and English. - **License detail:** Licensed under AGPL-3.0, which allows for free use, distribution, and modification as long as these rights are maintained in derivative works. ## Decision facts: Matcha-TTS - **Adopt for:** Matcha-TTS employs non-autoregressive probabilistic techniques with deep learning for fast TTS generation. ## Choose when ### Choose ChatTTS if… - ChatTTS is primarily Python; Matcha-TTS is Jupyter Notebook. - License: ChatTTS is AGPL-3.0, Matcha-TTS is MIT. - Requirements: Python-based implementation means that familiarity with Python is necessary for effective use.. - Tags unique to ChatTTS: agent, chatgpt, chattts, chinese language. - Also covers AI Agents. - Use ChatTTS when you require text-to-speech functionality for daily dialogue applications, especially those involving Chinese or English languages. ### Choose Matcha-TTS if… - Matcha-TTS is primarily Jupyter Notebook; ChatTTS is Python. - License: Matcha-TTS is MIT, ChatTTS is AGPL-3.0. - Tags unique to Matcha-TTS: deep-learning, diffusion-models, flow-matching, non-autoregressive. - When you require rapid deployment of text-to-speech engines without autoregressive dependencies ## When NOT to use ChatTTS - Avoid using ChatTTS in environments where the speech generation model is expected to handle complex technical jargon or specialized vocabulary, as it's optimized for daily conversation. - Do not use ChatTTS if your project requires the integration of more than two languages simultaneously due to its current support for only Chinese and English. ## When NOT to use Matcha-TTS - If your project requires real-time adaptability to user input that necessitates autoregressive methods - In scenarios where licensing flexibility is not a priority, favoring proprietary systems with dedicated support ## Common questions ### What is the difference between ChatTTS and Matcha-TTS? ChatTTS: A generative speech model for daily dialogue. Matcha-TTS: Matcha-TTS is a fast TTS architecture with conditional flow matching. See the comparison table for live GitHub stats and shared categories. ### When should I choose ChatTTS over Matcha-TTS? Choose ChatTTS over Matcha-TTS when ChatTTS is primarily Python; Matcha-TTS is Jupyter Notebook; License: ChatTTS is AGPL-3.0, Matcha-TTS is MIT; Requirements: Python-based implementation means that familiarity with Python is necessary for effective use.; Tags unique to ChatTTS: agent, chatgpt, chattts, chinese language; Also covers AI Agents; Use ChatTTS when you require text-to-speech functionality for daily dialogue applications, especially those involving Chinese or English languages. ### When should I choose Matcha-TTS over ChatTTS? Choose Matcha-TTS over ChatTTS when Matcha-TTS is primarily Jupyter Notebook; ChatTTS is Python; License: Matcha-TTS is MIT, ChatTTS is AGPL-3.0; Tags unique to Matcha-TTS: deep-learning, diffusion-models, flow-matching, non-autoregressive; When you require rapid deployment of text-to-speech engines without autoregressive dependencies. ### When should I avoid ChatTTS? Avoid using ChatTTS in environments where the speech generation model is expected to handle complex technical jargon or specialized vocabulary, as it's optimized for daily conversation. Do not use ChatTTS if your project requires the integration of more than two languages simultaneously due to its current support for only Chinese and English. ### When should I avoid Matcha-TTS? If your project requires real-time adaptability to user input that necessitates autoregressive methods In scenarios where licensing flexibility is not a priority, favoring proprietary systems with dedicated support ### Is ChatTTS or Matcha-TTS more popular on GitHub? ChatTTS has more GitHub stars (39,768 vs 1,339). Stars measure visibility, not whether either tool fits your constraints. ### Are ChatTTS and Matcha-TTS open source? Yes - both are open-source projects on GitHub (ChatTTS: AGPL-3.0, Matcha-TTS: MIT). ### Where can I find alternatives to ChatTTS or Matcha-TTS? GraphCanon lists graph-backed alternatives at [ChatTTS alternatives](/tools/2noise-chattts/alternatives) and [Matcha-TTS alternatives](/tools/shivammehta25-matcha-tts/alternatives) ([ChatTTS markdown twin](/tools/2noise-chattts/alternatives.md), [Matcha-TTS markdown twin](/tools/shivammehta25-matcha-tts/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/2noise-chattts-vs-shivammehta25-matcha-tts.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ChatTTS or Matcha-TTS? ChatTTS: Slowing. Matcha-TTS: 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 ChatTTS and Matcha-TTS? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ChatTTS trust report](/tools/2noise-chattts/trust); [Matcha-TTS trust report](/tools/shivammehta25-matcha-tts/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=2noise-chattts`](/api/graphcanon/graph?tool=2noise-chattts) - 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/_