--- title: "TTS vs FastChat" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/coqui-ai-tts-vs-lm-sys-fastchat" tools: ["coqui-ai-tts", "lm-sys-fastchat"] --- # TTS vs FastChat *GraphCanon updated Jul 11, 2026* ## Verdict Pick TTS when license: TTS is MPL-2.0, FastChat is Apache-2.0; pick FastChat when license: FastChat is Apache-2.0, 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. [FastChat](https://github.com/lm-sys/FastChat) has 39k stars, 4.8k forks, and 1.0k open issues, last pushed May 1, 2026. Figures are from public GitHub metadata via [TTS's repository](https://github.com/coqui-ai/TTS) and [FastChat's repository](https://github.com/lm-sys/FastChat). | | [TTS](/tools/coqui-ai-tts.md) | [FastChat](/tools/lm-sys-fastchat.md) | | --- | --- | --- | | Tagline | 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production | An open platform for training, serving, and evaluating large language models | | Stars | 45,737 | 39,490 | | Forks | 6,152 | 4,788 | | Open issues | 4 | 1,027 | | Language | Python | Python | | Adopt for | - | FastChat is a comprehensive open platform for managing large language models (LLMs) that includes capabilities for training, serving, evaluating, and comparing chatbot models via web UIs and RESTful APIs. It powers ChatB | | Persona | - | - | | Runtime | - | - | | License | MPL-2.0 | Apache-2.0 | | Categories | Inference & Serving, Model Training, Speech & Audio | Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [TTS](/tools/coqui-ai-tts.md) | [FastChat](/tools/lm-sys-fastchat.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Steady (60%) | | Days since push | 693d | 71d | | Open issues (now) | 4 | 1.0k | | Security scan | 137 low (137 low) | No lockfile | | Full report | [trust report](/tools/coqui-ai-tts/trust.md) | [trust report](/tools/lm-sys-fastchat/trust.md) | ## Shared compatibility - **Python**: [TTS](/tools/coqui-ai-tts.md) - Python runtime; [FastChat](/tools/lm-sys-fastchat.md) - Python runtime ## Decision facts: FastChat - **Adopt for:** FastChat is a comprehensive open platform for managing large language models (LLMs) that includes capabilities for training, serving, evaluating, and comparing chatbot models via web UIs and RESTful APIs. It powers ChatB ## Choose when ### Choose TTS if… - License: TTS is MPL-2.0, FastChat is Apache-2.0. - Tags unique to TTS: deep-learning, glow-tts, hifigan, melgan. - Also covers Speech & Audio. - TTS ships Docker support for self-hosted deployment. ### Choose FastChat if… - License: FastChat is Apache-2.0, TTS is MPL-2.0. - Tags unique to FastChat: chatbots, distributed serving, evaluation system, large-language-models. - Also covers Evaluation & Observability, LLM Frameworks. - - You are looking to train and evaluate state-of-the-art models such as Vicuna or MT-Bench. ## When NOT to use TTS - Last GitHub push was 694 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 FastChat - - You require a proprietary or closed-source framework; FastChat is open-source under Apache-2.0 license and its use might be unsuitable for environments requiring proprietary solutions. - - Your chatbot evaluation needs do not align with the types of data used in FastChat's datasets (e.g., human votes, MT-Bench evaluations). - - You prefer a more user-friendly setup without the need to clone a repository and manually install dependencies; FastChat requires installation from source with additional steps for Rust and CMake on - + Mac. ## Common questions ### What is the difference between TTS and FastChat? TTS: 🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production. FastChat: An open platform for training, serving, and evaluating large language models. See the comparison table for live GitHub stats and shared categories. ### When should I choose TTS over FastChat? Choose TTS over FastChat when License: TTS is MPL-2.0, FastChat is Apache-2.0; Tags unique to TTS: deep-learning, glow-tts, hifigan, melgan; Also covers Speech & Audio; TTS ships Docker support for self-hosted deployment. ### When should I choose FastChat over TTS? Choose FastChat over TTS when License: FastChat is Apache-2.0, TTS is MPL-2.0; Tags unique to FastChat: chatbots, distributed serving, evaluation system, large-language-models; Also covers Evaluation & Observability, LLM Frameworks; - You are looking to train and evaluate state-of-the-art models such as Vicuna or MT-Bench. ### When should I avoid TTS? Last GitHub push was 694 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 FastChat? - You require a proprietary or closed-source framework; FastChat is open-source under Apache-2.0 license and its use might be unsuitable for environments requiring proprietary solutions. - Your chatbot evaluation needs do not align with the types of data used in FastChat's datasets (e.g., human votes, MT-Bench evaluations). - You prefer a more user-friendly setup without the need to clone a repository and manually install dependencies; FastChat requires installation from source with additional steps for Rust and CMake on + Mac. ### Is TTS or FastChat more popular on GitHub? TTS has more GitHub stars (45,737 vs 39,490). Stars measure visibility, not whether either tool fits your constraints. ### Are TTS and FastChat open source? Yes - both are open-source projects on GitHub (TTS: MPL-2.0, FastChat: Apache-2.0). ### Where can I find alternatives to TTS or FastChat? GraphCanon lists graph-backed alternatives at [TTS alternatives](/tools/coqui-ai-tts/alternatives) and [FastChat alternatives](/tools/lm-sys-fastchat/alternatives) ([TTS markdown twin](/tools/coqui-ai-tts/alternatives.md), [FastChat markdown twin](/tools/lm-sys-fastchat/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-lm-sys-fastchat.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, TTS or FastChat? TTS: Dormant. FastChat: Steady. 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 FastChat? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [TTS trust report](/tools/coqui-ai-tts/trust); [FastChat trust report](/tools/lm-sys-fastchat/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/_