text-to-speech / voice cloning
GPT-SoVITS is a few-shot and zero-shot voice cloning text-to-speech system with a WebUI for training and inference.
Same problem, same approach. Swapping one for another is a config change, not a rewrite.
Choose it for Apache-2.0 licensing, full-stack training/deployment, and broad multilingual support.
Multi-lingual large voice generation model, providing inference, training and deployment full-stack ability.
Choose it for streaming generation and free-form voice design from the Qwen team.
Qwen3-TTS is an open-source series of TTS models developed by the Qwen team at Alibaba Cloud, supporting stable, expressive, and streaming speech generation, free-form voice design, and vivid voice cloning.
Choose it for 600+ language support, far broader than the seed's languages.
High-Quality Voice Cloning TTS for 600+ Languages
Choose it for high-quality expressive zero-shot TTS with open weights.
Zonos-v0.1 is a leading open-weight text-to-speech model trained on more than 200k hours of varied multilingual speech, delivering expressiveness and quality on par with—or even surpassing—top TTS providers.
Choose it for a lightweight, fast instant voice cloning model.
Instant voice cloning by MIT and MyShell. Audio foundation model.
Choose it for a dedicated multilingual and cross-lingual zero-shot TTS engine.
Confucius4-TTS: a Multilingual and Cross-Lingual Zero-Shot TTS Engine
Solves the same problem with a different architecture or at a different layer. Expect to rewrite the integration.
Choose it for ultra-fast inference at 150x realtime when speed is critical.
A high-quality rapid TTS voice cloning model that reaches speeds of 150x realtime.
Choose it if you want a TTS built by inverting Whisper, leveraging ASR's robustness.
An Open Source text-to-speech system built by inverting Whisper.
Choose it for a broader speech/sound generation model family beyond TTS.
An open-source model family for long-form speech, dialogue synthesis, voice design, sound effects, and real-time streaming TTS
An earlier or more limited way to do the job. Still the right call when you need something small, proven, or CPU-only.
Choose it when you need a zero-shot TTS and don't require few-shot fine-tuning, for a simpler pipeline.
An Industrial-Level Controllable and Efficient Zero-Shot Text-To-Speech System
Choose it if you already have a Spark-TTS model and need only inference, not training.
Spark-TTS Inference Code
Choose it if you specifically need MARS5's model, though it's older and less maintained.
MARS5 speech model (TTS) from CAMB.AI
Choose it for the historical VALL-E X zero-shot approach, but it's archived.
An open source implementation of Microsoft's VALL-E X zero-shot TTS model. Demo is available in https://plachtaa.github.io/vallex/
Choose it if you want the older MetaVoice expressive TTS, but updates are sparse.
Foundational model for human-like, expressive TTS
Does the same job, but ships as an app. Useful to a person, not swappable into a codebase.
Choose it as an end-user notebook for Bark voice cloning, if you prefer that model.
Bark Voice Cloning and Voice Cloning for Chinese Speech
Choose it as an end-user UI for XTTS-2 if you prefer that model over the seed.
A User Interface for XTTS-2 Text-Based Voice Cloning using only 10 seconds of speech
Choose it as a standalone app if you want a ready-to-use voice synthesis tool.
A Python/Pytorch app for easily synthesising human voices
These projects were analysed and named GPT-SoVITS among their alternatives. The relationship is not symmetric — how GPT-SoVITS rates them is a separate judgement, made when GPT-SoVITS is analysed in its own right.
calls GPT-SoVITS “Choose for few-shot voice cloning with your own data and an active community.”
SoTA open-source TTS
calls GPT-SoVITS “choose for a mature MIT-licensed few-shot voice cloning TTS with a large community.”
An Industrial-Level Controllable and Efficient Zero-Shot Text-To-Speech System
calls GPT-SoVITS “Choose when you have very little voice data (about 1 minute) and need rapid few-shot voice cloning under an MIT license.”
Multi-lingual large voice generation model, providing inference, training and deployment full-stack ability.
calls GPT-SoVITS “Choose when you need few-shot voice cloning from just 1 minute of audio and MIT license.”
Qwen3-TTS is an open-source series of TTS models developed by the Qwen team at Alibaba Cloud, supporting stable, expressive, and streaming speech generation, free-form voice design, and vivid voice cloning.
calls GPT-SoVITS “Use for MIT-licensed few-shot voice cloning with very small datasets and active community.”
High-Quality Voice Cloning TTS for 600+ Languages
calls GPT-SoVITS “choose over Zonos for MIT-licensed few-shot voice cloning with huge community resources and 1-minute custom adaptation; perhaps less polished for pure zero-shot.”
Zonos-v0.1 is a leading open-weight text-to-speech model trained on more than 200k hours of varied multilingual speech, delivering expressiveness and quality on par with—or even surpassing—top TTS providers.
calls GPT-SoVITS “A few-shot voice cloning TTS that trains on very little data; choose it when you need rapid adaptation with 1 minute of audio.”
🐸💬 - a deep learning toolkit for Text-to-Speech, battle-tested in research and production
calls GPT-SoVITS “choose when you have a few minutes of voice data and can fine-tune for higher quality on a specific voice.”
Instant voice cloning by MIT and MyShell. Audio foundation model.
calls GPT-SoVITS “Choose when you have extremely little data (1 min) and want high-quality few-shot cloning with active updates.”
🚀Clone a voice in 5 seconds to generate arbitrary speech in real-time
calls GPT-SoVITS “Choose when you need few-shot cloning from ~1 minute of audio, with strong Chinese/Japanese support.”
VoxCPM2: Tokenizer-Free TTS for Multilingual Speech Generation, Creative Voice Design, and True-to-Life Cloning
calls GPT-SoVITS “Choose when you need few-shot voice cloning with as little as 1 minute of data, as a standalone model/toolkit rather than a full webui.”
Gradio WebUI for creators and developers, featuring key TTS (Edge-TTS, kokoro) and zero-shot Voice Cloning (E2 & F5-TTS, CosyVoice), with Whisper audio processing, YouTube download, Demucs vocal isolation, and multilingual translation.
calls GPT-SoVITS “Choose when you have one minute of voice data and need few-shot voice cloning; local training pipeline.”
Use Microsoft Edge's online text-to-speech service from Python WITHOUT needing Microsoft Edge or Windows or an API key
calls GPT-SoVITS “choose when you need few-shot voice cloning with as little as 1 minute of reference audio and a larger community.”
Spark-TTS Inference Code
calls GPT-SoVITS “Choose when you need a focused few-shot voice cloning TTS with active development, while Amphion is a broader research toolkit.”
Amphion (/æmˈfaɪən/) is a toolkit for Audio, Music, and Speech Generation. Its purpose is to support reproducible research and help junior researchers and engineers get started in the field of audio, music, and speech generation research and development.
calls GPT-SoVITS “choose if you need strong few-shot cloning and can train/run heavy GPU models.”
A TTS that fits in your CPU (and pocket)
calls GPT-SoVITS “choose for few-shot voice cloning TTS with fast training and small data, if you don't need speech editing.”
Zero-Shot Speech Editing and Text-to-Speech in the Wild
calls GPT-SoVITS “choose for few-shot voice cloning from minimal data; not for predefined emotion prompts.”
EmotiVoice 😊: a Multi-Voice and Prompt-Controlled TTS Engine
calls GPT-SoVITS “choose for few-shot voice cloning from minimal data instead of full single-speaker training.”
VITS: Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech
calls GPT-SoVITS “Few-shot voice cloning from 1 minute of audio; ideal for personalized cloning rather than broad multi-lingual coverage.”
High-quality multi-lingual text-to-speech library by MyShell.ai. Support English, Spanish, French, Chinese, Japanese and Korean.
calls GPT-SoVITS “Choose for few-shot voice cloning with one minute of target speech if you do not need audio editing.”
A powerful 3B-parameter, LLM-based Reinforcement Learning audio edit model excels at editing emotion, speaking style, and paralinguistics, and features robust zero-shot text-to-speech