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What is Voxtral Mini TTS 3.0?

Voxtral Mini TTS 3.0, created by Mistral AI, serves as a specialized text-to-speech tool tailored for developers aiming to build applications and services that incorporate voice capabilities. This innovative model stands out by efficiently converting text into speech in both real-time and batch processing, providing features like preset and customizable voices, emotional tone adjustments, speed variations, and tailored pronunciation settings. It also boasts the ability to produce multilingual audio and accommodate different dialects, making it particularly suitable for uses such as interactive audio, localized media distribution, voice-driven interactions, and virtual assistant roles. Developers can seamlessly leverage its voice-cloning and speech generation abilities through Mistral's API. Moreover, Voxtral Mini TTS 3.0 is part of the larger Voxtral 3 voice-agent framework by Mistral, which includes capabilities for speech recognition, reasoning, tool application, and speech synthesis; this comprehensive system is designed to be deployed on clients' own infrastructures, granting developers enhanced flexibility and control. The continuous evolution of this model in voice synthesis technology signifies the potential for developers to craft richer and more immersive user experiences, further revolutionizing how voice interactions are integrated into various applications.

What is Voxtral?

Voxtral models are state-of-the-art open-source systems created for advanced speech understanding, offered in two distinct sizes: a larger 24 B variant intended for large-scale production and a smaller 3 B variant that is ideal for local and edge computing applications, both released under the Apache 2.0 license. These models stand out for their accuracy in transcription and their built-in semantic understanding, handling long-form contexts of up to 32 K tokens while also featuring integrated question-and-answer functions and structured summarization capabilities. They possess the ability to automatically recognize multiple languages among a variety of major tongues and facilitate direct function-calling to initiate backend operations via voice commands. Maintaining the textual advantages of their Mistral Small 3.1 architecture, Voxtral can manage audio inputs of up to 30 minutes for transcription and 40 minutes for comprehension tasks, consistently outperforming both open-source and proprietary rivals in renowned benchmarks such as LibriSpeech, Mozilla Common Voice, and FLEURS. Users can conveniently access Voxtral through downloads available on Hugging Face, API endpoints, or through private on-premises installations, while the model also offers options for specialized domain fine-tuning and advanced features tailored to enterprise requirements, greatly broadening its utility across diverse industries. Furthermore, the continuous enhancement of its functionality ensures that Voxtral remains at the forefront of speech technology innovation.

Media

Media

Integrations Supported

Mistral AI
LiveKit

Integrations Supported

Mistral AI
ExecuTorch
Hugging Face
LM Studio Bionic
LazyTyper
Vision Agents

API Availability

Has API

API Availability

Has API

Pricing Information

$13/1M chars
Speech generation costs $13 per 1 million characters.

Pricing Information

Pricing not provided

Supported Platforms

SaaS
On-Prem

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Online Training
On-Site Training

Company Facts

Organization Name

Mistral AI

Date Founded

2023

Company Location

France

Company Website

docs.mistral.ai/models/voxtral-mini-tts-3-0

Company Facts

Organization Name

Mistral AI

Date Founded

2023

Company Location

France

Company Website

mistral.ai/news/voxtral

Categories and Features

Text to Speech

Not specified

Categories and Features

AI Models

Not specified

Open-Weight AI Models

Not specified

Speech to Text

Not specified

Transcription

Not specified

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