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Chatterbox-TTS-Server

devnen/Chatterbox-TTS-Server

Self-host the Chatterbox TTS model with a user-friendly Web UI and flexible API endpoints

GitHub Website

GraphCanon updated 3w · GitHub synced 3w · 31 views this month

1.4k stars333 forksLast push 3mo Python MIT

Decision brief

Chatterbox-TTS-Server: Self-hostable TTS solution with Web UI, APIs, voice cloning, and large-scale text support across CUDA, ROCm, CPU.

Good fit when

You need a self-hosted Text-to-Speech service that supports advanced features like voice cloning.
Your project requires flexibility in API integration, including OpenAI-compatible endpoints.

Avoid when

When only pre-built wheels and no flexibility with Python versions is required (strictly follows Python 3.10).
If your hardware or OS lacks support detailed in the compatibility matrix, like unsupported GPUs/CPU setups.

Requirements:: Python 3.10 needed for pre-built wheels; avoid Python >=3.11 due to lack of support.; Ensure hardware and driver meets the Hardware Compatibility Matrix requirements.

Observed Jul 12, 2026 · Source: enrich:decision_facts

Chatterbox-TTS-Server alternatives Trust report

Verify the decision

Maintenance and security

Full trust report

Maintenance: Steady (64d since push); As of 3w
Provenance: Not a fork · Personal account; As of 3w
Security (OSV): 95 low (95 low); As of 1mo

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Install

pip install Chatterbox-TTS-Server

PyPI

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Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

Chatterbox-TTS-Server is a self-hostable text-to-speech solution providing a Web UI, APIs (including OpenAI compatible), voice cloning, and support for large-scale text processing. It supports NVIDIA (CUDA), AMD (ROCm), and CPU deployments.

Capability facts

Deploy: Self-host
Source: dockerfile:Dockerfile · Jul 30, 2026
Docker: Dockerfile present
Source: dockerfile:Dockerfile · Jul 30, 2026
Languages: python
Source: github.language · Jul 30, 2026

Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

Python runtimePython

Source: README excerpt (regex_v1, Jul 30, 2026)

- **Docker CPU:** New lightweight `Dockerfile.cpu` based on `python:3.10-slim` instead of the 4GB+ NVIDIA CUDA base image. `docker-compose-cpu.yml`

Source link

README

🖥️ Installation fixes across all platforms

All platforms: Chatterbox is now installed with --no-deps across all installation paths (CPU, NVIDIA, cu128, ROCm). This eliminates ONNX source build failures, torch version conflicts, and CMake errors that affected many users. Chatterbox's dependencies (conformer, diffusers, transformers, s3tokenizer, etc.) are now listed explicitly in each requirements file with onnx==1.16.0 pinned to guarantee pre-built wheels.
Apple Silicon / MPS: Fixed Turbo model crash ("Cannot convert a MPS Tensor to float64 dtype") by forcing float32 in s3tokenizer and voice_encoder. Fix applied in the chatterbox-v2 fork and also as an automatic post-install patch in start.py for users of other chatterbox versions. Thanks to @jonas3245 (#93).
Docker CPU: New lightweight Dockerfile.cpu based on python:3.10-slim instead of the 4GB+ NVIDIA CUDA base image. docker-compose-cpu.yml now uses this smaller image. Removed deprecated version tags from all docker-compose files.
config.yaml: Default device changed from cuda to auto for correct auto-detection on all hardware (CUDA, MPS, CPU).
Python version: Python 3.10 is required — it is the only version with pre-built wheels for all dependencies (torch, torchvision, ONNX). Python 3.11+ may fail due to missing wheels. The Windows launcher's Portable Mode handles this automatically by using an embedded Python 3.10 runtime.
Blackwell (CUDA 12.8): Fixed requirements-nvidia-cu128.txt to properly install PyTorch 2.9.0 with CUDA 12.8 (sm_120 support) for RTX 5060 Ti, 5070, 5070 Ti, 5080, and 5090 GPUs. The Dockerfile.cu128 now correctly installs chatterbox with --no-deps to prevent PyTorch downgrade.
AMD ROCm: Fixed ROCm installation by switching to PyTorch's official ROCm 6.1 wheel index (torch==2.5.1+rocm6.1), which resolves the previous torch==2.6.0 / torchaudio==2.5.1 version conflict. A new requirements-rocm-init.txt installs the ROCm PyTorch stack before other dependencies. Both Dockerfile.rocm and start.py now use a two-step install to prevent pip from replacing ROCm torch wheels with CPU-only versions.
Thanks to community contributors in issues #20, #23, #44, #58, #64, #79, #89, #92, #93, #98, #105, #107, #109, #113, #114, #121, and #122 for testing and reporting solutions.

Hardware Compatibility Matrix

Hardware	Installation Option	Requirements File	Driver Requirement
CPU Only	`--cpu`	requirements.txt	None
NVIDIA RTX 20/30/40	`--nvidia`	requirements-nvidia.txt	525+
NVIDIA RTX 5090 / Blackwell (sm_120)	`--nvidia-cu128`	requirements-nvidia-cu128.txt (torch 2.9, CUDA 12.8)	570+
NVIDIA DGX Spark / GB10 (sm_121)	Docker only	requirements-nvidia-cu130.txt (torch 2.10, CUDA 13.0)	580+
AMD RX 6000/7000 (Linux)	`--rocm`	requirements-rocm.txt	ROCm 6.4+
AMD Strix Halo (Ryzen AI MAX+)	Docker only	requirements-strixhalo.txt (ROCm 7.2)	ROCm 7.2+
AMD RX 9000 series / RDNA4 (Linux)	Docker only	requirements-rdna4-init.txt (ROCm 7.2)	ROCm 7.2+
Apple Silicon (M1/M2/M3/M4)	Manual install	See Option 4	macOS 12.3+

💻 Installation and Setup

This project uses specific dependency files to ensure a smooth installation for your hardware. You can choose between the automated launcher (recommended for most users) or manual installation (for advanced users).

1. Clone the Repository

git clone https://github.com/devnen/Chatterbox-TTS-Server.git
cd Chatterbox-TTS-Server

🚀 Quick Start with Automated Launcher (Recommended)

The automated launcher handles virtual environment creation, hardware detection, dependency installation, and server startup - all in one step.

Windows


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# Skip menu and install NVIDIA CUDA 12.1 directly
python start.py --nvidia

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# Upgrade to l

For agents

This page has a .md twin and JSON over the API.

/tools/devnen-chatterbox-tts-server.md GET /api/graphcanon/tools/devnen-chatterbox-tts-server GET /api/graphcanon/graph?tool=devnen-chatterbox-tts-server