Simon Willison — 2026-04-27#
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The most substantive post for developers today is Simon’s hands-on experiment running Microsoft’s VibeVoice model locally via MLX. It’s a great example of his signature workflow: taking a newly accessible open-source AI model and immediately figuring out the most frictionless CLI one-liner to get it running on Apple Silicon.
Posts#
[microsoft/VibeVoice] · Source
Simon explores Microsoft’s MIT-licensed VibeVoice, a Whisper-style speech-to-text model that notably includes built-in speaker diarization. He shares a practical one-liner using uv and mlx-audio to run a 4-bit quantized version locally on a Mac. Testing it against a one-hour podcast interview, it transcribed the audio in under 9 minutes and impressively distinguished between the host’s conversational voice and his “sponsor read” voice. You’ll need to manually split audio files longer than an hour to avoid token limits, but the resulting JSON drops nicely into Datasette Lite for browsing.