---
title: "Chatterbox-TTS-Server vs FastChat"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/devnen-chatterbox-tts-server-vs-lm-sys-fastchat"
tools: ["devnen-chatterbox-tts-server", "lm-sys-fastchat"]
---

# Chatterbox-TTS-Server vs FastChat

*GraphCanon updated Jul 11, 2026*

## Verdict

Pick Chatterbox-TTS-Server when license: Chatterbox-TTS-Server is MIT, FastChat is Apache-2.0; pick FastChat when license: FastChat is Apache-2.0, Chatterbox-TTS-Server is MIT.

[Chatterbox-TTS-Server](https://colab.research.google.com/github/devnen/Chatterbox-TTS-Server/blob/main/Chatterbox_TTS_Colab_Demo.ipynb) reports 1.3k GitHub stars, 323 forks, and 43 open issues, last pushed May 26, 2026. [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 [Chatterbox-TTS-Server's repository](https://github.com/devnen/Chatterbox-TTS-Server) and [FastChat's repository](https://github.com/lm-sys/FastChat).

| | [Chatterbox-TTS-Server](/tools/devnen-chatterbox-tts-server.md) | [FastChat](/tools/lm-sys-fastchat.md) |
| --- | --- | --- |
| Tagline | Self-host the powerful Chatterbox TTS model. This server offers a user-friendly Web UI, flexible API endpoints (incl. OpenAI compatible), predefined voices, voice cloning, and large audiobook-scale te | An open platform for training, serving, and evaluating large language models |
| Stars | 1,348 | 39,490 |
| Forks | 323 | 4,788 |
| Open issues | 43 | 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 | MIT | Apache-2.0 |
| Categories | Inference & Serving, Model Training, Vector Databases | Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training |

## Trust and health

_Sourced signals - not a safety guarantee. No winner column._

| | [Chatterbox-TTS-Server](/tools/devnen-chatterbox-tts-server.md) | [FastChat](/tools/lm-sys-fastchat.md) |
| --- | --- | --- |
| Days since push | 45d | 71d |
| Open issues (now) | 43 | 1.0k |
| Owner type | User | Organization |
| Security scan | 95 low (95 low) | No lockfile |
| Full report | [trust report](/tools/devnen-chatterbox-tts-server/trust.md) | [trust report](/tools/lm-sys-fastchat/trust.md) |

## Shared compatibility

- **Python**: [Chatterbox-TTS-Server](/tools/devnen-chatterbox-tts-server.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 Chatterbox-TTS-Server if…

- License: Chatterbox-TTS-Server is MIT, FastChat is Apache-2.0.
- Tags unique to Chatterbox-TTS-Server: ai, api-server, audio-generation, chatterbox.
- Also covers Vector Databases.
- Chatterbox-TTS-Server ships Docker support for self-hosted deployment.

### Choose FastChat if…

- License: FastChat is Apache-2.0, Chatterbox-TTS-Server is MIT.
- 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 Chatterbox-TTS-Server

- 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.
- Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.

## 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 Chatterbox-TTS-Server and FastChat?

Chatterbox-TTS-Server: Self-host the powerful Chatterbox TTS model. This server offers a user-friendly Web UI, flexible API endpoints (incl. OpenAI compatible), predefined voices, voice cloning, and large audiobook-scale te. 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 Chatterbox-TTS-Server over FastChat?

Choose Chatterbox-TTS-Server over FastChat when License: Chatterbox-TTS-Server is MIT, FastChat is Apache-2.0; Tags unique to Chatterbox-TTS-Server: ai, api-server, audio-generation, chatterbox; Also covers Vector Databases; Chatterbox-TTS-Server ships Docker support for self-hosted deployment.

### When should I choose FastChat over Chatterbox-TTS-Server?

Choose FastChat over Chatterbox-TTS-Server when License: FastChat is Apache-2.0, Chatterbox-TTS-Server is MIT; 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 Chatterbox-TTS-Server?

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. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.

### 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 Chatterbox-TTS-Server or FastChat more popular on GitHub?

FastChat has more GitHub stars (39,490 vs 1,348). Stars measure visibility, not whether either tool fits your constraints.

### Are Chatterbox-TTS-Server and FastChat open source?

Yes - both are open-source projects on GitHub (Chatterbox-TTS-Server: MIT, FastChat: Apache-2.0).

### Where can I find alternatives to Chatterbox-TTS-Server or FastChat?

GraphCanon lists graph-backed alternatives at [Chatterbox-TTS-Server alternatives](/tools/devnen-chatterbox-tts-server/alternatives) and [FastChat alternatives](/tools/lm-sys-fastchat/alternatives) ([Chatterbox-TTS-Server markdown twin](/tools/devnen-chatterbox-tts-server/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/devnen-chatterbox-tts-server-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, Chatterbox-TTS-Server or FastChat?

Chatterbox-TTS-Server: Steady. 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 Chatterbox-TTS-Server and FastChat?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Chatterbox-TTS-Server trust report](/tools/devnen-chatterbox-tts-server/trust); [FastChat trust report](/tools/lm-sys-fastchat/trust).

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/graph?tool=devnen-chatterbox-tts-server`](/api/graphcanon/graph?tool=devnen-chatterbox-tts-server)
- 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/_
