Voxtral: Mistral AI's Open Source Whisper Alternative

For the past few years, OpenAI's Whisper has reigned as the undisputed champion of open-source speech recognition. It offered a level of accuracy that democratized automatic speech recognition (ASR) for developers, researchers, and hobbyists worldwide. It was a monumental leap forward, but the community has been eagerly awaiting the next step—a model that goes beyond mere transcription into the realm of true understanding. That wait is now over. Mistral AI has entered the ring with Voxtral, a new suite of open-source models that isn’t just an alternative to Whisper; it's the new standard.

Voxtral is a direct answer to the limitations of previous-generation ASR. While Whisper excelled at converting speech to text, it left the heavy lifting of semantic interpretation to other models. Building truly intelligent voice applications required a clunky and often inefficient process of chaining Whisper's output into a separate Large Language Model (LLM). Mistral AI’s Voxtral shatters this paradigm by integrating state-of-the-art transcription and deep language understanding into a single, cohesive, and open-source powerhouse.

Outperforming the Champion: A New Leader in Transcription

The first and most critical test for any Whisper alternative is transcription accuracy. On this front, Voxtral delivers a decisive victory. Mistral AI's benchmarks show that Voxtral comprehensively outperforms Whisper large-v3, the previous open-source leader. It doesn’t stop there; it also surpasses proprietary models like GPT-4o mini Transcribe and Gemini 2.5 Flash across a wide range of tasks.

Specifically, Voxtral establishes state-of-the-art results in English short-form transcription and on the multilingual Mozilla Common Voice benchmark. When evaluated across multiple languages in the FLEURS benchmark, Voxtral Small outperforms Whisper on every single task, showcasing its superior multilingual capabilities, especially in European languages. This isn't an incremental improvement; it's a fundamental step up in raw performance, available to everyone under the permissive Apache 2.0 license.

From Transcription to True Understanding

The real revolution of Voxtral lies in its ability to natively understand the content it transcribes. This is where it leaves traditional ASR models like Whisper far behind. Voxtral is not just a speech-to-text engine; it's a speech-to-meaning engine.

This is made possible through a suite of built-in capabilities:

Integrated Q&A and Summarization: With Voxtral, there is no need to pipe a transcript into another model to ask questions or get a summary. You can interact directly with the audio content. This is enabled by its massive 32k token context window, which allows it to process and analyze up to 30 minutes of audio for transcription or 40 minutes for understanding tasks. This is ideal for summarizing long meetings, analyzing lectures, or pulling key insights from podcasts without a complex multi-step process.

Function-Calling Directly From Voice: This is a capability that places Voxtral in a class of its own. It can interpret spoken commands and directly trigger backend functions or API calls. Imagine a user saying, "Add 'buy milk' to my shopping list," and the model directly interfacing with a task-management app. This transforms voice from a passive input into an active, actionable command interface, something Whisper was never designed to do.

Natively Multilingual Intelligence: While Whisper has multilingual support, Voxtral’s performance is a clear step ahead. With automatic language detection and state-of-the-art results in languages from Hindi to Dutch, it provides a single, powerful system for building global applications.

Powerful Text Capabilities: Because Voxtral is built on the backbone of Mistral Small 3.1, it retains all the powerful text-based reasoning and generation capabilities of its parent LLM. This makes it a versatile, two-in-one model for both audio and text tasks.

Bridging the Gap: Open Source Freedom, Premium Performance

The ASR market has long been defined by a trade-off. On one side, you had open-source models like Whisper, which offered freedom and control but lagged behind the top proprietary APIs in performance and features. On the other, you had closed-source APIs that offered higher performance but at a significant cost and with no control over the underlying model.

Voxtral bridges this gap completely. It delivers performance that is not only superior to the leading open-source model but also competitive with or better than the best proprietary APIs. And it does this while remaining fully open-source.

For those who prefer a managed service, Mistral’s API pricing for Voxtral is a direct challenge to the market, costing less than half the price of comparable APIs from competitors like OpenAI and ElevenLabs. This combination of superior open-source performance and disruptive pricing makes high-quality speech intelligence accessible to all.

Get Started with the New Standard

Mistral AI has made it incredibly easy to start building with Voxtral. The models are available in two sizes: a 24B variant for production-scale use and a nimble 3B variant perfect for the edge and local applications where smaller Whisper models were often used.

Download the Models: Both Voxtral (24B) and Voxtral Mini (3B) are available on Hugging Face for anyone to download and use.

Use the API: Integrate Voxtral into any application with a simple API call.

Try the Demo: Experience Voxtral’s capabilities directly in Le Chat, Mistral’s web and mobile chat interface.

Whisper laid the foundation for a new generation of open-source AI. It was a crucial and celebrated step. But the field moves fast, and with the release of Voxtral, a new benchmark has been set. Offering superior transcription, deep semantic understanding, and a feature set designed for building truly interactive applications, Voxtral is more than just an alternative—it's the successor. The future of open-source voice AI is here, and its name is Voxtral.