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Explore This 164MB Speech Model Might Replace Whisper... with 116,219 views, 1,611 likes, and 76 comments. Experience the impact of this video content that has captured audience attention.

Phonon-2 is a new 164MB open-source speech-to-text model from Fermion Research that claims to transcribe an entire hour of audio in just 21 seconds on a MacBook Air, completely offline. In this video, I test Phonon-2 on Apple Silicon, walk through the installation and Python CLI, and compare its transcription speed, accuracy, and word error rate against Whisper, Redux, and the original NVIDIA Parakeet model. 🔗 Relevant Links Phonon-2 - https://www.fermionresearch.com/models/phonon-2/ Hugging Face Phonon-2 - https://huggingface.co/FermionResearch/Phonon-2 ❤️ More about us Radically better observability stack: https://betterstack.com/ Written tutorials: https://betterstack.com/community/ Example projects: https://github.com/BetterStackHQ 📱 Socials Twitter: https://twitter.com/betterstackhq Instagram: https://www.instagram.com/betterstackhq/ TikTok: https://www.tiktok.com/@betterstack LinkedIn: https://www.linkedin.com/company/betterstack 📌 Chapters: 00:00 Phonon-2: 164MB Speech Model, 21-Second Transcription 00:31 Phonon-2 vs Parakeet Redux: What's Different? 01:36 Installing Phonon-2 on Mac & Transcription Demo 02:39 How Phonon-2 Achieves 174x Real-Time Speed 03:14 Accuracy Test: Phonon-2 vs Whisper vs Redux 04:03 The Catch With Phonon-2's Benchmarks 05:25 Independent Speech-to-Text Benchmark Results 06:20 Live Transcription, Captions & Custom Hotwords 07:18 Running a Local OpenAI-Compatible Transcription API 08:00 Phonon-2 Licensing, Commercial Use & Limitations 08:49 Phonon-2 vs Whisper vs Redux: Which Is Best?

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