Voxtral Transcribe 2 Review: How It Compares to Whisper and ScreenApp

Mistral just dropped Voxtral Transcribe 2, and the speech-to-text landscape got a lot more interesting. Released on February 5, 2026, this new model family includes Voxtral Mini Transcribe V2 for batch processing and Voxtral Realtime for live transcription with sub-200ms latency. With open weights under Apache 2.0 and pricing at $0.003 per minute, it is the most aggressive play yet in the transcription API market.

But raw model benchmarks only tell part of the story. If you need to transcribe meetings or record and transcribe live audio, what actually matters is the full experience: accuracy in real conversations, ease of use, speaker identification, and what happens after the transcript is generated. Let’s break down how Voxtral compares to Whisper, ScreenApp, and other leading transcription tools.

What Is Voxtral Transcribe 2?

Voxtral Transcribe 2 is a family of two speech-to-text models built by Mistral AI. The first model, Voxtral Mini Transcribe V2, handles batch transcription. You upload an audio file (up to 3 hours), and it returns a transcript with speaker labels, word-level timestamps, and context biasing for domain-specific terminology. It supports 13 languages including English, Spanish, French, German, Japanese, Korean, Chinese, Hindi, Arabic, Portuguese, Russian, Italian, and Dutch.

The second model, Voxtral Realtime, is purpose-built for live transcription. Unlike batch models that process audio in chunks, Realtime uses a streaming architecture that transcribes audio as it arrives. The delay is configurable down to sub-200ms, which makes it fast enough for voice agents, live subtitles, and real-time meeting transcription.

Mistral claims Voxtral Mini Transcribe V2 achieves approximately 4% word error rate on the FLEURS benchmark, outperforming GPT-4o mini Transcribe, Gemini 2.5 Flash, AssemblyAI Universal, and Deepgram Nova. It also processes audio roughly 3x faster than ElevenLabs Scribe v2 while matching on quality at one-fifth the cost.

Voxtral Realtime is released under the Apache 2.0 license, meaning you can download the weights from Hugging Face and run it on your own hardware. The 4B parameter model is small enough to run on edge devices, which is a big deal for privacy-sensitive deployments.

Voxtral vs Whisper

OpenAI’s Whisper has been the default open-source transcription model since its release in 2022. The large-v3 variant is still widely used, and OpenAI offers a managed API at $0.006 per minute. Here is how the two compare.

Whisper large-v3 reports approximately 10.3% word error rate on multilingual benchmarks, while Voxtral claims around 4% on FLEURS. That is a significant gap, though benchmark numbers should always be taken with some caution since real-world accuracy depends heavily on audio quality, accents, and domain.

Whisper’s managed API does not include speaker diarization. You need to combine it with a separate diarization pipeline (like pyannote) or use a third-party service that wraps Whisper with diarization added on top. Voxtral includes diarization natively in the batch model, which simplifies the pipeline considerably.

On pricing, Whisper’s managed API costs $0.006 per minute. Voxtral Mini Transcribe V2 costs $0.003 per minute, exactly half the price. Voxtral Realtime costs $0.006 per minute, matching Whisper’s batch pricing but offering live streaming capability.

Whisper is available as open-source weights you can self-host, and so is Voxtral Realtime. However, Voxtral Mini Transcribe V2 (the batch model) is API-only for now. If you are self-hosting for cost reasons, Whisper still has a larger ecosystem of optimized inference tools (faster-whisper, WhisperX, whisper.cpp).

The context biasing feature in Voxtral is notable. You can pass up to 100 words or phrases to guide the model toward correct spellings of names, technical terms, or jargon. Whisper does not offer anything equivalent through its API.

Voxtral vs Cloud Services

Beyond open-source models, several cloud transcription services compete in this space. AssemblyAI, Deepgram, and Rev are among the most popular. Here is where Voxtral fits.

AssemblyAI’s Universal model offers strong accuracy with features like sentiment analysis, topic detection, and entity recognition built into the pipeline. Pricing is $0.0037 per second ($0.222 per minute) for their best model, which is significantly more expensive than Voxtral. However, AssemblyAI provides a much richer post-processing layer.

Deepgram Nova offers competitive pricing and speed, with their API starting at $0.0043 per minute for pre-recorded audio. Deepgram’s strength is its customization options and low-latency streaming. Voxtral Realtime competes directly with Deepgram’s streaming offering, and the sub-200ms latency claim would put it in a similar tier.

Rev combines AI transcription with human review options. Their AI-only tier starts at $0.02 per minute, while human-verified transcription costs more. Rev is a good choice if you need guaranteed accuracy, but it is considerably more expensive than Voxtral for pure AI transcription.

The key difference is that Voxtral is a model, not a platform. It gives you a transcript, timestamps, and speaker labels. It does not give you a searchable archive, AI summaries, action items, or any workflow around the transcript. For that, you need to build your own pipeline or use a product that handles the full workflow.

Voxtral vs ScreenApp

This is where the comparison shifts from models to products. ScreenApp is not a transcription model. It is a complete meeting and recording platform that uses AI transcription as one component of a larger workflow.

When you record a meeting with ScreenApp, the platform handles the entire pipeline: recording, transcription with speaker diarization, AI-generated summaries, action items, searchable archives, and sharing. You do not need to think about which model is running underneath.

ScreenApp works directly in your browser with no software to install, no API keys to manage, and no infrastructure to maintain. It integrates with Zoom, Google Meet, Microsoft Teams, and other platforms. The transcription happens automatically, and you get a structured output you can search, export, and share.

For developers building voice applications, Voxtral is genuinely exciting. The combination of low latency, low cost, and open weights makes it an excellent foundation for custom voice pipelines. But for professionals who need meeting transcription, lecture notes, or interview records, a product like ScreenApp removes all the complexity.

Here is a practical example. If you use Voxtral’s API to transcribe a one-hour meeting, you get a text transcript with speaker labels and timestamps. Total cost: $0.18. But then you need to: store it somewhere, make it searchable, generate a summary, extract action items, and share it with your team. Each of those steps requires additional tooling.

With ScreenApp, you click record, attend your meeting, and everything else happens automatically. The AI note taker generates structured notes. The transcript is searchable. You can share a link with your team. The total experience is fundamentally different from working with a raw transcription API.

Comparison Table

Who Should Use Voxtral?

Voxtral Transcribe 2 is best suited for developers and engineering teams building voice-powered applications. If you are creating a voice agent, live subtitling system, call center automation, or any product that needs a transcription layer, Voxtral gives you a strong model at a competitive price.

The open-weights release of Voxtral Realtime is particularly valuable for privacy-sensitive deployments. Healthcare, legal, and financial applications that cannot send audio to third-party APIs can run the model on their own infrastructure. The 4B parameter size makes this feasible even on consumer-grade hardware.

For individual professionals, content creators, and teams who need meeting transcription as part of their workflow, a product like ScreenApp is a better fit. You get transcription plus everything that comes after: summaries, notes, search, and collaboration. The value is in the complete workflow, not just the transcript.

The Bigger Picture

VentureBeat declared 2026 “the year of note-taking,” and it is easy to see why. The cost of high-quality transcription has dropped by an order of magnitude in just two years. Voxtral at $0.003 per minute means transcribing an eight-hour workday costs $1.44. That changes the economics of recording and transcribing everything.

This matters because cheaper transcription enables new workflows. When transcription is expensive, you only transcribe important meetings. When it costs almost nothing, you can transcribe every conversation, every brainstorming session, every quick call. The challenge shifts from “can we afford to transcribe this?” to “how do we make all these transcripts useful?”

That is exactly where tools like ScreenApp add value. Raw transcription is becoming a commodity. The differentiation is in what happens after: intelligent summaries, searchable archives, automated follow-ups, and seamless sharing. As the underlying models get cheaper and better, the products built on top of them become more important, not less.

Getting Started

If you want to try Voxtral Transcribe 2, head to Mistral’s audio playground to test it with your own audio files. For production use, the API is available through Mistral’s platform at $0.003 per minute for batch and $0.006 per minute for real-time.

If you want transcription that works out of the box with no setup, try ScreenApp’s online transcript generator. Upload any audio or video file, or record directly in your browser. You get a transcript with speaker labels, an AI summary, and structured notes in minutes.

FAQ

Is Voxtral Transcribe 2 free?

Voxtral Realtime is open-weights under Apache 2.0, so you can download and run it for free on your own hardware. The API costs $0.006 per minute. Voxtral Mini Transcribe V2 is API-only at $0.003 per minute.

How accurate is Voxtral compared to Whisper?

Mistral reports approximately 4% word error rate on the FLEURS benchmark for Voxtral Mini Transcribe V2, compared to approximately 10.3% for Whisper large-v3. Real-world results depend on audio quality and domain.

Does Voxtral support speaker diarization?

Yes, Voxtral Mini Transcribe V2 includes built-in speaker diarization with precise start and end times for each speaker. Voxtral Realtime does not currently support diarization.

Can I use Voxtral for meeting transcription?

You can use the API to transcribe meeting audio, but you would need to build your own pipeline for recording, storing, summarizing, and sharing. For an all-in-one solution, tools like ScreenApp handle the full workflow.

What languages does Voxtral support?

Voxtral supports 13 languages: English, Chinese, Hindi, Spanish, Arabic, French, Portuguese, Russian, German, Japanese, Korean, Italian, and Dutch.

Is Voxtral better than AssemblyAI or Deepgram?

Voxtral offers lower pricing than both, and Mistral claims higher accuracy on benchmarks. However, AssemblyAI and Deepgram provide richer platform features like sentiment analysis, topic detection, and custom vocabulary training. The right choice depends on whether you need a model or a platform.