--- title: "TTS vs fastDeploy" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/coqui-ai-tts-vs-notai-tech-fastdeploy" tools: ["coqui-ai-tts", "notai-tech-fastdeploy"] --- # TTS vs fastDeploy *GraphCanon updated Jul 15, 2026* ## Verdict Pick TTS when license: TTS is MPL-2.0, fastDeploy is MIT; pick fastDeploy when license: fastDeploy is MIT, TTS is MPL-2.0. [TTS](http://coqui.ai) reports 46k GitHub stars, 6.2k forks, and 4 open issues, last pushed Aug 16, 2024. [fastDeploy](https://github.com/notAI-tech/fastDeploy) has 105 stars, 17 forks, and 0 open issues, last pushed Feb 10, 2026. Figures are from public GitHub metadata via [TTS's repository](https://github.com/coqui-ai/TTS) and [fastDeploy's repository](https://github.com/notAI-tech/fastDeploy). | | [TTS](/tools/coqui-ai-tts.md) | [fastDeploy](/tools/notai-tech-fastdeploy.md) | | --- | --- | --- | | Tagline | 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production | Deploy DL/ ML inference pipelines with minimal extra code. | | Stars | 45,737 | 105 | | Forks | 6,152 | 17 | | Open issues | 4 | 0 | | Language | Python | Python | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | MPL-2.0 | MIT | | Categories | Inference & Serving, Model Training, Speech & Audio | Inference & Serving, Model Training, Speech & Audio | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [TTS](/tools/coqui-ai-tts.md) | [fastDeploy](/tools/notai-tech-fastdeploy.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Slowing (36%) | | Days since push | 693d | 154d | | Open issues (now) | 4 | 0 | | Full report | [trust report](/tools/coqui-ai-tts/trust.md) | [trust report](/tools/notai-tech-fastdeploy/trust.md) | ## Choose when ### Choose TTS if… - License: TTS is MPL-2.0, fastDeploy is MIT. - Tags unique to TTS: glow-tts, hifigan, melgan, multi-speaker-tts. - TTS ships Docker support for self-hosted deployment. ### Choose fastDeploy if… - License: fastDeploy is MIT, TTS is MPL-2.0. - Tags unique to fastDeploy: docker, falcon, gevent, gunicorn. - More recently updated (last pushed Feb 10, 2026). ## When NOT to use TTS - Last GitHub push was 698 days ago (dormant maintenance, Aug 16, 2024). Validate activity before betting a new project on TTS. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ## When NOT to use fastDeploy - Last GitHub push was 155 days ago (slowing maintenance, Feb 10, 2026). Validate activity before betting a new project on fastDeploy. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ## Common questions ### What is the difference between TTS and fastDeploy? TTS: 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production. fastDeploy: Deploy DL/ ML inference pipelines with minimal extra code.. See the comparison table for live GitHub stats and shared categories. ### When should I choose TTS over fastDeploy? Choose TTS over fastDeploy when License: TTS is MPL-2.0, fastDeploy is MIT; Tags unique to TTS: glow-tts, hifigan, melgan, multi-speaker-tts; TTS ships Docker support for self-hosted deployment. ### When should I choose fastDeploy over TTS? Choose fastDeploy over TTS when License: fastDeploy is MIT, TTS is MPL-2.0; Tags unique to fastDeploy: docker, falcon, gevent, gunicorn; More recently updated (last pushed Feb 10, 2026). ### When should I avoid TTS? Last GitHub push was 698 days ago (dormant maintenance, Aug 16, 2024). Validate activity before betting a new project on TTS. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ### When should I avoid fastDeploy? Last GitHub push was 155 days ago (slowing maintenance, Feb 10, 2026). Validate activity before betting a new project on fastDeploy. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ### Is TTS or fastDeploy more popular on GitHub? TTS has more GitHub stars (45,737 vs 105). Stars measure visibility, not whether either tool fits your constraints. ### Are TTS and fastDeploy open source? Yes - both are open-source projects on GitHub (TTS: MPL-2.0, fastDeploy: MIT). ### Where can I find alternatives to TTS or fastDeploy? GraphCanon lists graph-backed alternatives at [TTS alternatives](/tools/coqui-ai-tts/alternatives) and [fastDeploy alternatives](/tools/notai-tech-fastdeploy/alternatives) ([TTS markdown twin](/tools/coqui-ai-tts/alternatives.md), [fastDeploy markdown twin](/tools/notai-tech-fastdeploy/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/coqui-ai-tts-vs-notai-tech-fastdeploy.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, TTS or fastDeploy? TTS: Dormant. fastDeploy: 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 TTS and fastDeploy? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [TTS trust report](/tools/coqui-ai-tts/trust); [fastDeploy trust report](/tools/notai-tech-fastdeploy/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=coqui-ai-tts`](/api/graphcanon/graph?tool=coqui-ai-tts) - 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/_