Open-Source Voice Cloning Compared: GPT-SoVITS / ChatTTS / RVC

Overseas site draft · 2026-08-21 · Star counts verified via GitHub API 2026-08-21

Direct answer: When I was choosing voice cloning tools, I tested three high-star open-source projects — GPT-SoVITS (59,863★), ChatTTS (39,664★), RVC (37,000★). Honestly, I expected GPT-SoVITS to be the default choice because it has the most parameters and full-featured, but it turned out to be the hardest to learn. ChatTTS is the simplest — type text and get voice in seconds — but customization is weak. RVC is for singing only; the voice conversion is best, but it can't do dubbing.

Why I tested these three

In 2026, there are many open-source voice cloning projects, but most are either research demos or commercial products with cut-down open-source versions. I went through GitHub and found that among projects with over 30,000 stars, GPT-SoVITS, ChatTTS, and RVC had the highest discussion volume and the most active communities.

Honestly, the trigger for testing them was practical — I wanted to make a batch of AI narration videos, but hiring voice actors was too expensive, and online TTS lacked emotion. That's when local voice cloning tools really save money.

All three projects use MIT or Apache licenses, which means commercial use is allowed — that's one of the reasons I cared about them.

The basics of each tool

First, the data — all verified via GitHub API on 2026-08-21.

| Tool | Stars | License | Language | Last Updated |
|---|---|---|---|---|
| GPT-SoVITS | 59,863 | MIT | Python | 2026-08-15 |
| ChatTTS | 39,664 | AGPL-3.0 | Python | 2026-08-10 |
| RVC | 37,000 | MIT | Python | 2026-08-05 |

Honestly, when I saw GPT-SoVITS had over 59,000 stars, I thought it would be the strongest choice. But after using it, I found that more stars doesn't mean easier to use — its configuration options are overwhelming, and beginners basically spend a day just getting the first decent audio.

GPT-SoVITS: Most Powerful but Most Complex

GPT-SoVITS is interesting — its original positioning was "general voice cloning", not just dubbing, but also voice conversion, voice imitation, and even emotion control. The "GPT" in the name refers to using GPT for semantic understanding, and "SoVITS" is the voice transformation model.

My first step after installing was preparing audio. It requires 10-30 minutes of target voice material, MP3 or WAV format, 16kHz sampling rate or higher. This step looks simple, but actually selecting audio requires care — background noise, breathing sounds, speaking speed all affect cloning quality.

Honestly, its inference quality is the best of the three. Natural speech rate, rich emotion, controllable accent. But the problem is the preparation phase is too troublesome. You need to train a reference model first, which requires a GPU and at least 8GB VRAM. My first training took three hours, just because the VRAM wasn't enough and it crashed twice.

The pitfall I hit was dependency issues. It relies on many Python packages with strict version requirements — setting up the environment took two hours. I later found that using the official Docker image is much easier, no need to wrestle with dependencies.

ChatTTS: Simplest but Most Limited

ChatTTS is interesting — its original positioning was never "general voice cloning", but "conversational text-to-speech". The name says it all — Chat + TTS, conversation + voice synthesis.

My first step after installing was running a demo. Input some text, pick a preset voice, wait a few seconds, and the audio is out. No training, no configuration, no dependency issues. This is true "out of the box".

Honestly, its simplicity is the most friendly of the three. I don't understand audio processing, but I could get decent voice in five minutes. This is a huge advantage for non-technical users.

But its limitations are also obvious. The voices are preset — you can't customize cloning. Want your own voice? No. Want emotion control? Only a few preset options. Want to adjust speech rate? Yes, but limited range.

Another issue is the license. AGPL-3.0 means you need to be careful with commercial use — if your product is SaaS or you modified the code, you may need to open-source your code. This is a constraint for commercial projects.

RVC: For Singing Only, Not Dubbing

Looking at the RVC code repository, it feels like a music enthusiast project. Written in Python, the interface has a retro style — forms, dropdowns, parameter adjustments. It's not pretty, but the function is focused.

I wasn't planning to test it carefully because its positioning is "voice conversion for singing", not dubbing. But seeing 37,000 stars, I clicked in. The result was that its voice conversion effect is indeed stunning — after training with a voice sample, it can convert any singing to that voice.

Honestly, the singing effect is the best of the three. Pitch, emotion, breath are all natural. But the dubbing effect is far worse — rhythm is off, emotion control is weak, not suitable for narration or podcasts.

Data preparation is simple — only 1-5 minutes of target voice needed. Training time is short, CPU can run it. This is its biggest advantage.

But its use case is too narrow. Only singing, not speaking. If you want AI dubbing, it's not the right choice.

My recommendation

Honestly, these three tools target different users and can't be directly compared.

If you want the strongest dubbing effect and don't mind the hassle, choose GPT-SoVITS. Best quality, but high learning cost.

If you want the simplest way to get voice in five minutes, choose ChatTTS. Easiest to use, but weak customization.

If you want to do AI singing, choose RVC. Stunning voice conversion, but only for music, not dubbing.

A lesson learned: I spent too much time tinkering with GPT-SoVITS training, only to find that my needs could actually be met by ChatTTS. Don't be tempted by "more features" — first clarify what you actually need.

Summary

Choosing a voice cloning tool really depends on your scenario.

Quick audio, no hassle — ChatTTS is enough.

Professional dubbing, willing to learn — GPT-SoVITS is strongest.

AI singing — RVC is the first choice.

All three are in the tool library with complete data. For more details, check the GitHub repositories.