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Open Source Text to Speech Models

Every TTS model on our platform is open source with commercially-friendly licenses. MIT, Apache 2.0 — no proprietary lock-in, no usage restrictions, no surprise licensing fees. Use them through our hosted API, or self-host them on your own infrastructure with full control.

Open Source MIT License Apache 2.0 Self-Hostable GitHub မှ
အပြည့်အဝ TTS တည်းဖြတ်သူ API စာရွက်စာတမ်း

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Free with Kokoro, Piper, VITS, MeloTTS
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Open Source TTS Benefits

Why open-source models matter for your projects

All Open-Source Licensed

Every model on TTS.ai uses a permissive open-source license. No proprietary black boxes, no vendor lock-in, no unexpected licensing fees.

MIT / Apache 2.0

Models are licensed under MIT or Apache 2.0, the most permissive open-source licenses. Use commercially, modify, redistribute — no restrictions.

Self-Hostable

Download any model and run it on your own hardware. Full control over your data, latency, and infrastructure. No cloud dependency required.

GPU Optimized

Models are optimized for NVIDIA GPUs with CUDA support. Piper runs on CPU only. Most models need 2-8GB VRAM for efficient inference.

Community Maintained

Active open-source communities maintain and improve these models. Contributions welcome — submit bugs, improvements, and new voices on GitHub.

Commercial Use OK

All models allow commercial use under their licenses. Build products, sell services, and create commercial content with no royalties or usage fees.

Our Open Source Model Catalog

Every model, its license, and what it does best

KokoroKokoro

Free

Lightweight 82M parameter model delivering studio-quality speech with blazing-fast inference.

Fast 5/5

အကောင်းဆုံး: Apache 2.0 — best quality free model, 82M params, easy to self-host

စမ်းကြည့်ပါ Kokoro

PiperPiper

Free

A fast, local neural text to speech system optimized for Raspberry Pi and embedded devices.

Fast 3/5

အကောင်းဆုံး: MIT — CPU-only, perfect for edge devices and embedded self-hosting

စမ်းကြည့်ပါ Piper

VITSVITS

Free

Conditional variational autoencoder with adversarial learning for end-to-end text-to-speech.

Fast 3/5

အကောင်းဆုံး: MIT — foundational architecture used by many downstream models

စမ်းကြည့်ပါ VITS

BarkBark

Standard

Transformer-based text-to-audio model that generates realistic speech, music, and sound effects.

Slow 4/5

အကောင်းဆုံး: MIT — unique audio generation capabilities beyond standard TTS

စမ်းကြည့်ပါ Bark

Tortoise TTSTortoise TTS

Premium

Multi-voice text-to-speech focused on quality with autoregressive architecture.

Slow 5/5 အသံခိုးယူခြင်း

အကောင်းဆုံး: Apache 2.0 — maximum quality, widely studied reference implementation

စမ်းကြည့်ပါ Tortoise TTS

OpenVoiceOpenVoice

Premium

Instant voice cloning with granular control over style, emotion, and accent.

Medium 4/5 အသံခိုးယူခြင်း

အကောင်းဆုံး: MIT — open-source voice cloning with granular style control

စမ်းကြည့်ပါ OpenVoice

How to Use Open Source TTS

Use our hosted API or run models yourself

1

Explore Open-Source Models

Browse our catalog of 20+ open-source TTS models. Each model page shows the license, architecture, capabilities, and self-hosting requirements.

2

Try in Your Browser

Test any model directly on TTS.ai without installing anything. Our GPU servers handle processing so you can evaluate quality before committing to self-hosting.

3

Self-Host or Use Our API

Clone model repos from GitHub and run locally, or use our hosted API for production. Self-hosting gives full control; our API provides managed infrastructure.

4

Build Your Application

Integrate TTS into your product using self-hosted models or our REST API. All models are commercially usable with no licensing fees or royalties.

License Comparison

All models on TTS.ai use commercially-friendly open-source licenses

Model License Commercial Use Modification Self-Host Attribution
Kokoro Apache 2.0 Required
Piper MIT Optional
VITS MIT Optional
MeloTTS MIT Optional
Chatterbox MIT Optional
Tortoise TTS Apache 2.0 Required
StyleTTS 2 MIT Optional
OpenVoice MIT Optional
Sesame CSM Apache 2.0 Required
Orpheus Llama 3.2 "Built with Llama"

Self-Hosting vs Hosted API

Run models yourself or let us handle the infrastructure

Self-Host on Your Hardware

Every model on TTS.ai is available as an open-source project on GitHub or Hugging Face. Download the weights, install the dependencies, and run inference on your own GPUs. You have full control over latency, privacy, and scaling.

  • Full data privacy — audio never leaves your server
  • No per-request costs after initial setup
  • Custom fine-tuning on your own data
  • Requires GPU hardware (NVIDIA recommended)
  • You manage updates, scaling, and dependencies

Use TTS.ai Hosted API

Get instant access to all 24+ models through a single REST API. We handle GPU provisioning, model updates, queue management, and scaling. One API key gives you access to every model — no need to manage separate deployments.

  • No GPU hardware needed
  • All 24+ models through one API
  • Automatic model updates and improvements
  • 99.9% uptime with redundant infrastructure
  • Pay only for what you use

Quick Start: API or Self-Host

Use our hosted API, or install Kokoro locally in minutes

Option 1: TTS.ai Hosted API Easiest 
import requests

response = requests.post("https://api.tts.ai/v1/tts", json={
    "text": "Open source TTS with a simple API.",
    "model": "kokoro",
    "voice": "af_heart",
    "format": "wav"
}, headers={"Authorization": "Bearer YOUR_API_KEY"})

with open("output.wav", "wb") as f:
    f.write(response.content)
Option 2: Self-Host with pip Full Control 
# Install Kokoro locally
pip install kokoro

# Generate speech on your own GPU
import kokoro

pipeline = kokoro.KPipeline(lang_code="a")
generator = pipeline("Hello from your own server!", voice="af_heart")
for i, (gs, ps, audio) in enumerate(generator):
    kokoro.save(audio, f"output_{i}.wav")

Open Source, Affordable Pricing

Our hosted API makes open-source TTS accessible without managing GPUs.

Free Tier

$0

50 credits on signup

  • 4 open-source models free
  • No signup for basic use
  • Commercial use allowed

Starter

$9

500 credits/month

  • All 24+ open-source models
  • Voice cloning
  • API access

Pro

$29

2000 credits/month

  • Priority GPU processing
  • All premium models
  • Enterprise support
View Full Pricing

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Common questions about open source text to speech

Yes. Every model on TTS.ai uses a permissive open-source license — either MIT or Apache 2.0. We specifically exclude models with restrictive licenses (like Coqui's CPML or non-commercial CC-BY-NC). You can verify each model's license on its GitHub repository.

Both are permissive open-source licenses allowing commercial use, modification, and redistribution. Apache 2.0 adds explicit patent grants and requires stating changes if you modify the code. MIT is simpler with fewer requirements. Both are business-friendly.

Yes. Every model can be self-hosted. Clone the model repository from GitHub, install dependencies, download model weights, and run inference. We provide documentation for each model's self-hosting requirements including GPU, RAM, and Python version.

Requirements vary by model. Piper needs no GPU (CPU only). Kokoro and MeloTTS need 1-2GB VRAM. Most standard models need 4GB VRAM. Tortoise and Sesame CSM need 8GB. An NVIDIA RTX 3060 (12GB) can run most models comfortably.

Yes. Open-source licenses allow modification including fine-tuning. Models like GPT-SoVITS and Bark provide fine-tuning scripts. You can train models on your own voice data to create custom voices or improve performance for specific languages.

Top open-source models (Kokoro, StyleTTS 2, Chatterbox) now match or exceed commercial services like ElevenLabs and Google TTS in quality benchmarks. The main advantage of commercial services is managed infrastructure and support, not audio quality.

We have already excluded them. XTTS/XTTS-v2 (Coqui's CPML — non-commercial), F5-TTS (CC-BY-NC — non-commercial), and Higgs-v2 (Boson License — restrictive) were all removed. Every model on TTS.ai is verified commercial-use safe.

Yes. Most models accept community contributions via GitHub. You can submit bug reports, voice recordings for new languages, code improvements, and documentation. Check each model's GitHub repository for contribution guidelines and active issues.

Load models on-demand and unload when idle to share GPU memory. Our GPU server runs 20+ models on 4x Tesla P40 (96GB total VRAM) using dynamic loading. For self-hosting, a single 24GB GPU can serve 3-5 models concurrently.

Many models provide official Docker images or Dockerfiles. For running multiple models, you can build a custom Docker setup with NVIDIA Container Toolkit for GPU access. Our API server architecture can serve as a reference implementation.

Most models require Python 3.10-3.12. Coqui TTS (VITS) specifically needs Python 3.11. We recommend Python 3.12 for most models. Check each model's requirements.txt for exact version compatibility.

Yes. MIT and Apache 2.0 licenses explicitly allow commercial use. You can build SaaS products, mobile apps, games, and services using these models with no licensing fees, royalties, or attribution requirements (though attribution is appreciated).
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Try Open Source TTS Today

24+ open-source models, all commercially-licensed. Use our API or self-host — the choice is yours.

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