Why We Replaced Whisper 2.0 with Deepgram 2.0 and Cut Voice Transcription Costs by 45%
The article discusses the migration from OpenAI Whisper 2.0 to Deepgram 2.0 for voice transcription services. This switch resulted in a 45% reduction in monthly costs and improved performance metrics. The decision was driven by increasing transcription volume and limitations experienced with Whisper.
- ▪The team processed 12 million minutes of voice transcription and cut costs by 45% after migrating to Deepgram 2.0.
- ▪Deepgram 2.0 showed a 12% improvement in Word Error Rate compared to Whisper 2.0.
- ▪Monthly transcription expenses decreased from $42,000 to $23,100 with no increase in support tickets.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3900225) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } ANKUSH CHOUDHARY JOHAL Posted on Apr 28 • Originally published at johal.in Why We Replaced Whisper 2.0 with Deepgram 2.0 and Cut Voice Transcription Costs by 45% #replaced #whisper #deepgram #voice After processing 12 million minutes of voice transcription across 14 global regions in Q3 2024, our team cut monthly infrastructure costs by 45% by migrating from OpenAI Whisper 2.0 to Deepgram 2.0 – with a 12% improvement in WER (Word Error Rate) and 60% lower p99 latency.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at DEV Community.
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