Popular Open-Source Text-to-Speech Models in 2026

You’re building something intelligent, something that thinks. But then you realise… it should speak too, not robotic but truly human-like. A product with a voice that connects, guides and responds across languages, platforms and users.

From AI assistants and customer-support bots to voice-enabled apps and multilingual agents, text-to-speech has become an important part of modern AI pipelines. But as shiny as the proprietary tools may look but the price tags can grow fast. Limits, tokens and hidden constraints. 

But with open-source TTS models, you can run, fine-tune and deploy your way. No lock-ins but you get flexibility, performance and innovation. Our latest blog walks you through the popular open-source text-to-speech models and how to choose the right one for your stack.

What is a Text-to-Speech Model

A text-to-speech (TTS) model converts written text into spoken audio using AI. It understands language, tone and pronunciation to generate natural-sounding speech. Modern open-source TTS models allow developers to create custom voices, multilingual assistants, accessibility tools and voice experiences across apps, devices and platforms, often without licensing restrictions.

What to Consider Before Choosing a Text-to-Speech Model

Here’s what you should know before choosing an open-source TTS model:

Natural Voice Quality 

You must evaluate how real and human-like the generated speech sounds. Pay attention to tone, pronunciation, pacing and whether the voices feel robotic or natural. For production use, clarity and emotions in voice are important.

Language and Accent Support

You should know whether the model supports the languages and accents your project requires. Some TTS systems excel in English, while others specialise in multilingual output which is crucial for global apps, e-learning platforms and accessibility tools.

Resource Requirements and Deployment

You must consider whether the model can run efficiently in your environment (for example, cloud or locally). Some models need powerful GPUs, whereas lightweight options exist for embedded devices or offline use.

Voice Cloning 

If you need custom voices such as brand-specific voice assistants or cloned voices, ensure the model supports voice training or cloning. 

Community, Documentation and Ecosystem

You should ensure the project has active development, good documentation and community support. Strong ecosystems mean easier troubleshooting, faster development, more voice samples and better long-term reliability.

Popular Open-Source Text-to-Speech Models

Now that you know the considerations, it’s time to explore the popular open-source TTS models. Each TTS model below offers different features and the right choice will depend on your use case and project needs.

XTTS-v2 

XTTS-v2 is an advanced open-source text-to-speech model developed by Coqui AI that enables high-quality, multilingual voice synthesis and zero-shot voice cloning from just a brief audio clip (about 6 seconds). It supports 17 languages, including English, Spanish, Hindi, Dutch, Russian and more. The model also offers cross-language voice transfer and supports emotion/style transfer for expressive output. 

Mozilla TTS

Mozilla TTS is a powerful open-source text-to-speech framework developed by the Mozilla Foundation that enables natural and high-quality speech synthesis across multiple languages and voice styles. It supports deep learning architectures like Tacotron and WaveRNN for realistic voice generation.

With a rich set of pre-trained models and training recipes, Mozilla TTS is ideal for research, accessibility projects and custom voice development.

ChatTTS

ChatTTS is an open-source text-to-speech model purpose-built for conversational scenarios like chatbots or dialogue with large language models (LLMs). It supports English and Chinese, offers multi-speaker voices and is optimised for tasks such as virtual assistants and interactive voice experiences. One of its best features is fine-grained control of prosody (pauses, laughter and interjections), making the speech feel more natural and dynamic. 

MeloTTS

MeloTTS is an open-source, high-quality multilingual text-to-speech library developed by MyShell.ai with contributions from researchers at MIT. It supports varied accents in English (American, British, Indian, Australian) as well as Spanish, French, Chinese (including mixed English/Chinese), Japanese and Korean. The model is optimised for real-time inference even on CPUs.

Coqui TTS 

Coqui TTS is a comprehensive open-source deep-learning toolkit for text-to-speech synthesis, offering pretrained models in 1100+ languages and tools for training or fine-tuning new voices. It’s designed for both research and production use, providing dataset utilities, speaker embeddings and support for multiple architectures. Because of its flexibility and large language coverage, it is ideal for global applications, accessibility, voice assistants and multilingual deployments.

Bark TTS

Bark, created by Suno AI, is a transformer-based open-source text-to-audio model that goes beyond standard speech: it can generate highly realistic multilingual speech and non-verbal sounds such as laughter, sighing, crying, background noise and simple music. This TTS model can deliver up to 2× faster generation on GPUs and as much as a 10× speed-up on CPUs.

Bark has recently moved to the MIT licence for full commercial use. The model now also supports GPUs with under 4 GB VRAM, making high-quality creative audio generation even more accessible.

Conclusion

Open-source TTS models can narrate, chat, emote, clone and create. But having the right model is only half the story. The real magic happens when you run them at scale without worrying about infrastructure slowing you down. That's when you think about choosing the right cloud GPU provider.

Your models have a voice. Now give them the cloud power they deserve.

With Hyperstack, you can spin up GPUs in minutes, train voice models without powerful NVIDIA A100/NVIDIA H100/NVIDIA RTX A6000 GPU VMs and fine-tune expressive speech with high-performance compute, storage and deployment. You don’t need to worry about vendor lock-ins or unpredictable bills. Hyperstack gives you the performance, flexibility and cost-efficiency to turn text into emotion, speech and experience.

Access high-performance acceleration on Hyperstack, designed for builders who want their AI to speak just as powerfully as it thinks.

FAQs

What is a text-to-speech (TTS) model?

A text-to-speech (TTS) model converts written text into spoken audio. It uses AI to understand language, tone and pronunciation, generating natural-sounding speech for applications such as voice assistants, chatbots, accessibility tools and multilingual content experiences.

Why choose open-source TTS models over proprietary ones?

Open-source TTS models offer flexibility, transparency and cost efficiency. They allow customisation, fine-tuning and deployment without vendor lock-ins or restrictive pricing. Developers can build at scale, adapt models to different languages and run workloads on their own infrastructure or cloud GPUs.

Which open-source TTS models are best today?

Some of the top open-source TTS models include XTTS-v2, Mozilla TTS, ChatTTS, MeloTTS, Coqui TTS and Bark TTS. Each model offers unique strengths such as multilingual support, voice cloning, conversational prosody and fast offline deployment, depending on your requirements.

Why deploy TTS workloads on cloud GPUs?

Cloud GPUs provide the compute power needed for real-time speech generation, fast training and high-quality voice synthesis. Cloud platforms enable scalability, faster experimentation, flexible resource allocation and reduced upfront hardware costs, especially for production-grade TTS pipelines.