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Whisper Large v3 Turbo Overview

Whisper Large v3 Turbo (openai/whisper-large-v3-turbo) is the fastest high-accuracy automatic speech recognition (ASR) model from OpenAI — a pruned and fine-tuned version of Whisper large-v3 that runs about 8x faster with minimal word-error-rate degradation. At just 809M parameters, it delivers near-large-v3 transcription quality at a fraction of the compute, ideal for real-time and large-scale transcription.

• 8x Faster than large-v3: A distilled architecture with only 4 decoder layers (down from 32) delivers roughly 8x faster inference with negligible WER change.
• 809M Parameters: About half the size of whisper-large-v3 (1.55B), cutting memory and compute cost while keeping near-state-of-the-art accuracy.
• 32K Context Window: A 32,000-token context handles up to ~22 minutes of audio per pass for efficient long-form transcription.
• 99 Languages: Multilingual speech recognition and translation to English, trained on over 5M hours of weakly supervised data.
• Rich Timestamps: Returns segment-level and word-level timestamps for precise captioning, subtitling, and subtitle generation workflows.
• Broad Runtime Support: Runs in Hugging Face Transformers, faster-whisper, whisper.cpp, MLX, and the openai-whisper CLI with fp16 and INT8 quantization options.
• Strong Robustness: Generalizes well to accents, background noise, and technical language with zero-shot speech translation into English.
• Open Source: MIT licensed and freely downloadable from Hugging Face with an active open ecosystem.