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  1. Home
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  4. VITS
open sourcespeech

VITS

Foundational free TTS — natural human voice from text in one step

Developed by Kakao Enterprise

Try Model
~33MParams
YesAPI
stableStability
VITS / VITS2Version
MITLicense
PyTorchFramework
YesRuns Local

Playground

Implementation Example

Example Prompt

user input
Text: 'Welcome to our podcast — today we explore the future of artificial intelligence.' Voice: Female English (LJSpeech).

Model Output

model response
Returns a 5-second 22.05 kHz WAV file with natural female English narration matching the prompt — generated in ~0.4 seconds on a laptop CPU. Real-time factor better than 10x on a modern GPU.

Examples

Real-World Applications

  • Audiobook narration
  • video voiceovers
  • accessibility tools
  • language preservation
  • embedded voice assistants
  • custom-voice chatbots
  • educational TTS.

Docs

Model Intelligence & Architecture

What is VITS?

VITS (Variational Inference with adversarial learning for end-to-end Text-to-Speech) is a foundational text-to-speech model published in 2021 by researchers at Kakao Enterprise (South Korea). Unlike older two-stage TTS systems (which generate spectrograms then waveforms separately), VITS is a true end-to-end model producing natural-sounding speech audio directly from text in one step.

VITS implementations are released under MIT license, free for commercial use.

Why VITS Is Still Relevant in 2026

Although newer models like XTTS, OpenVoice, and ElevenLabs surpass VITS in expressiveness, the original VITS architecture remains the foundation of nearly every modern open-source TTS system. Coqui TTS, MaiNoji, and many community models are direct descendants of VITS.

Key Features and Capabilities

VITS supports end-to-end TTS, multi-speaker training, language adaptation, fast inference (real-time on CPU), and natural prosody. It uses a normalizing-flow-based VAE combined with adversarial training for high-quality audio.

Who Should Use VITS?

VITS is ideal for indie developers, researchers, hobbyists, accessibility tool builders, language preservation projects, and anyone needing simple TTS.

Top Use Cases

Real-world applications include audiobook narration, video voiceovers, accessibility tools, language preservation TTS, voice assistants for embedded devices, custom-voice chatbots, and educational content.

Where Can You Run It?

VITS runs on Coqui TTS, ESPnet, official VITS GitHub, Hugging Face Transformers, and Mozilla TTS forks. The base model is tiny (~150 MB) and runs in real-time on CPU.

How to Use VITS (Quick Start)

Easiest path via Coqui TTS: pip install TTS, then tts --text 'Hello world' --model_name 'tts_models/en/ljspeech/vits' --out_path output.wav. For training a custom voice, prepare 1-3 hours of clean recordings and follow the Coqui training guide.

When Should You Choose VITS?

Choose VITS when you need simple, fast, MIT-licensed TTS as a starting point or for resource-constrained deployment. For higher-quality voice cloning, use OpenVoice or XTTS v2.

Pricing

VITS is completely free under MIT license.

Pros and Cons

Pros: ✔ MIT license ✔ End-to-end architecture ✔ Tiny ~150MB model ✔ Real-time on CPU ✔ Foundation of modern open TTS ✔ Multi-speaker support

Cons: ✘ Less expressive than newer models ✘ Voice cloning weaker than OpenVoice ✘ Limited prosody control ✘ Pronounced training-data accent

Final Verdict

VITS is the foundational open-source TTS model that still powers countless deployments in 2026. Discover more voice AI at FreeAPIHub.com.

Evaluation

Advantages & Limitations

Advantages
  • ✓ MIT license
  • ✓ End-to-end architecture
  • ✓ Tiny ~150MB model
  • ✓ Real-time on CPU
  • ✓ Foundation of modern open TTS
  • ✓ Multi-speaker support
Limitations
  • ✗ Less expressive than newer models
  • ✗ Voice cloning weaker than OpenVoice
  • ✗ Limited prosody control
  • ✗ Pronounced training-data accent

Important Notice

Verify Before You Decide

Last verified · Apr 29, 2026

The details on this page — including pricing, features, and availability — are based on our last review and may not reflect the provider's current offering. Providers update their products frequently, sometimes without prior notice.

What may have changed

Pricing Plans
Features & Limits
Availability
Terms & Policies

Always visit the official provider website to confirm the latest pricing, terms, and feature availability before subscribing or integrating.

Check official site

External Resources

Try the Model Official Website Source Code

Technical Details

Architecture
End-to-end VAE + Normalizing Flow + Adversarial training
Stability
stable
Framework
PyTorch
License
MIT
Release Date
2021-06-11
Signup Required
No
API Available
Yes
Runs Locally
Yes

Rate Limits

No limits self-hosted

Pricing

Completely free under MIT license

Best For

Indie developers and researchers needing simple, lightweight, MIT-licensed TTS

Alternative To

Tacotron 2, FastSpeech 2 (older), Coqui XTTS

Compare With

vits vs xttsvits vs tacotron 2vits vs openvoicefree tts modelopen source text to speech

Tags

#TTS#VITS#Speech Synthesis#Audio Generation#Open Source AI#text-to-speech

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