Mistral
Voxtral
Mistral
Mistral Launches Voxtral, Open-Source Audio AI That Beats Whisper and GPT-4o Mini
Mistral has introduced Voxtral, its first open-source AI model for speech transcription and audio understanding. The model family includes Voxtral Small with 24 billion parameters and Voxtral Mini with 3 billion parameters, featuring context windows of up to 40 minutes. Voxtral challenges closed-source leaders by delivering better accuracy at half the typical API costs. Enterprises and developers now have a cost-effective, multilingual alternative for voice-based applications.
Georg S. Kuklick
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July 16, 2025
Mistral AI has entered the audio AI market with the release of Voxtral, an open-source family of large audio models built for transcription, summarization, and audio-based Q&A. Released under the permissive Apache 2.0 license, Voxtral is production-ready and targets enterprises building speech interfaces without vendor lock-in. The lineup includes Voxtral Small for server deployment and Voxtral Mini designed for lightweight, edge-device inference.
Performance benchmarks position Voxtral as a strong competitor to proprietary services. According to Mistral, Voxtral Small outperforms OpenAI’s Whisper large-v3, GPT-4o mini Transcribe, Gemini 2.5 Flash, and ElevenLabs Scribe. The model supports transcription of up to 30 minutes and audio understanding across 40-minute contexts. It offers multilingual capabilities in English, French, Spanish, Portuguese, Hindi, and more. Mistral claims Voxtral’s API costs less than $0.001 per minute, slashing costs by more than half compared to commercial rivals.
The launch positions Mistral as a serious contender in the speech AI market. Voxtral provides an open-source option for businesses building voice applications, from automated call center transcription to real-time assistants and media analysis. By combining high accuracy, long context windows, and cost efficiency, Voxtral challenges incumbents relying on proprietary models and creates fresh opportunities for AI builders.
