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Whisper Large V3 Turbo

whisper-large-v3-turbo
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INPUT
Audio
OUTPUT
Text
CAPABILITIES
JSON Object Mode, Speech to Text
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Model card

Whisper Large v3 Turbo is OpenAI's fastest speech recognition model optimized for speed while maintaining high accuracy. This model delivers exceptional performance with optimized speed, high accuracy across diverse audio conditions, and multilingual support. Built on OpenAI's optimized transformer architecture, it features streamlined processing for enhanced speed while preserving the core capabilities of the Whisper family. The model incorporates efficiency improvements and optimizations that reduce computational overhead without sacrificing transcription quality, making it perfect for time-sensitive applications.

PRICING

Per Hour
$0.04

LIMITS

MAX FILE SIZE
100 MB

QUANTIZATION

This uses Groq's TruePoint Numerics, which reduces precision only in areas that don't affect accuracy, preserving quality while delivering significant speedup over traditional approaches. Learn more here.

Key Technical Specifications

Model Architecture

Based on OpenAI's optimized transformer architecture, Whisper Large v3 Turbo features streamlined processing for enhanced speed while preserving the core capabilities of the Whisper family. The model incorporates efficiency improvements and optimizations that reduce computational overhead without sacrificing transcription quality, making it perfect for time-sensitive applications.

Performance Metrics

Whisper Large v3 Turbo delivers excellent performance with optimized speed:
  • Fastest processing in the Whisper family
  • High accuracy across diverse audio conditions
  • Multilingual support: 99+ languages
  • Optimized for real-time transcription
  • Reduced latency compared to standard models

Key Model Details

  • Model Size: Optimized architecture for speed
  • Speed: 216x speed factor
  • Audio Context: Optimized for 30-second audio segments, with a minimum of 10 seconds per segment
  • Supported Audio: FLAC, MP3, M4A, MPEG, MPGA, OGG, WAV, or WEBM
  • Language: 99+ languages supported
  • Usage: Groq Speech to Text Documentation

Use Cases

Real-Time Applications
Perfect for applications requiring immediate transcription:
  • Live streaming and broadcast captioning
  • Real-time meeting transcription and note-taking
  • Interactive voice applications and assistants
High-Volume Processing
Ideal for scenarios requiring fast processing of large amounts of audio:
  • Batch processing of audio content libraries
  • Customer service call transcription at scale
  • Media and entertainment content processing
Cost-Effective Solutions
Excellent for budget-conscious applications:
  • Startups and small businesses needing affordable transcription
  • Educational platforms with high usage volumes
  • Content creators requiring frequent transcription services

Best Practices

  • Optimize for speed: Use this model when fast transcription is the primary requirement
  • Leverage cost efficiency: Take advantage of the lower pricing for high-volume applications
  • Real-time processing: Ideal for applications requiring immediate speech-to-text conversion
  • Balance speed and accuracy: Perfect middle ground between ultra-fast processing and high precision
  • Multilingual efficiency: Fast processing across 99+ supported languages

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