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Vorstellung von Mistral Voxtral: Revolutionäre Open-Source-Sprach-KI

2. August 2025
8 min read
Whisper Notes Team

Mistral released Voxtral—their first native speech recognition models. They're open-source and competitive with GPT-4o Audio at a fraction of the cost. Here's what the research shows and why Whisper Notes still uses Whisper Large-v3 Turbo for offline transcription.

Mistral Voxtral Performance Benchmarks

Two Models

Mistral released two versions:

Voxtral Small

  • 12B parameters
  • Higher accuracy, handles noise really well
  • Slower, more resource-intensive
  • Perfect for complex audio

Voxtral Mini

  • Way smaller, way faster
  • Real-time processing
  • Lower hardware requirements
  • Works on edge devices

Open Source

Voxtral is open-source. Unlike GPT-4o Audio, you can download and run it yourself:

  • Full model weights available
  • Deploy anywhere, modify as needed
  • No API costs or vendor lock-in
  • Process audio on your own servers

Benchmarks

WER (Word Error Rate) comparison shows Voxtral Small beats GPT-4o Audio—lower is better:

Voxtral WER Benchmark Comparison across all models

WER comparison across speech recognition models

Model WER (English) Multilingual WER Processing Speed
Voxtral Small 2.1% 3.8% Fast
Voxtral Mini 3.2% 4.9% Very Fast
GPT-4o Audio 2.8% 4.1% Slow
Whisper Large v3 2.4% 3.9% Medium

Pricing

Voxtral costs 92% less than GPT-4o Audio:

Voxtral Small

$0.20
per million tokens

GPT-4o Audio

$2.50
per million tokens

Cost Savings

92%
vs GPT-4o Audio

How It Works

Mistral's research paper explains the key innovations:

1. Multimodal Architecture

Voxtral processes speech and text together instead of handling them separately:

  • Understands speech and context simultaneously
  • Handles audio up to 2 hours long
  • Adapts to accents and background noise in real time

Streaming Encoder

Processes audio in 30ms chunks with 200ms latency—fast enough for real-time meetings and interviews.

2. Training Dataset

Large multilingual dataset with real-world conditions:

  • 2.3 million hours of speech across 108 languages
  • Trained on noisy audio, reverb, compression artifacts
  • Continuous learning without forgetting previous training

3. Efficiency Optimizations

Technical improvements for way faster inference:

  • Flash Attention v3—70% less memory, faster processing
  • Adjusts compute based on audio complexity
  • 4-bit quantization with minimal accuracy loss (< 0.1% WER increase)

4. Key Features

Contextual Understanding

Maintains context across entire conversations—perfect for meetings, interviews, and long recordings.

Multilingual

Supports 108 languages with auto-detection. Handles code-switching within the same audio seamlessly.

Noise Handling

Automatically adapts to reverb, echo, and background noise.

Edge Deployment

Runs on edge devices with just 4GB RAM—enables on-device transcription.

5. Architecture

Three main components:

  1. 1. Audio Encoder: Conformer-based encoder converts audio to acoustic representations
  2. 2. Multimodal Fusion: Cross-attention aligns audio with text understanding
  3. 3. Language Decoder: Based on Mistral's LLM, fine-tuned for speech

This setup gives good accuracy while staying efficient enough for real deployment.

Why Whisper Notes Still Makes Sense

Voxtral is impressive, but Whisper Notes is a way better fit for personal use:

What Whisper Notes Offers

Privacy

  • 100% offline processing
  • No data transmission
  • No cloud dependencies

Performance

  • Whisper technology, proven accuracy
  • Optimized for Apple Silicon
  • Reliable results

Cost

  • $4.99 once
  • No per-minute charges
  • Unlimited transcription

User Experience

  • Simple interface
  • Regular updates
  • Continuous improvements

Storage Requirements

Voxtral isn't practical for most personal users. Even Voxtral Mini needs over 9GB of storage and way more VRAM than most consumer Macs can handle efficiently.

Whisper Notes uses Whisper Large-v3 Turbo—it balances performance, speed, and VRAM requirements for everyday use. We'll upgrade to better models when they become available with reasonable resource requirements.

Voxtral is perfect for developers and cloud apps. Whisper Notes is way better for individual users who want privacy, reliability, and zero subscriptions.

What This Means

Voxtral is a big step forward for speech recognition. Open-source models like this will push the industry forward fast.

For now, Whisper Notes is still a way better choice for private, offline transcription on Mac and iPhone.

Try Whisper Notes

Offline transcription for iPhone and Mac. $4.99 once, no subscription.

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Whisper Notes

Offline Sprache-zu-Text Transkriptions iOS/macOS App mit Whisper KI. Wandeln Sie Sprachmemos, Audioaufnahmen, Meetings und Vorlesungen privat auf Ihrem iPhone/Mac in Text um. Keine Internetverbindung erforderlich. Über 80 Sprachen unterstützt.

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