Moonshine Open-Weights STT models – higher accuracy than WhisperLargev3
I wanted to share our new speech to text model, and the library to use them effectively. We're a small startup (six people, sub-$100k monthly GPU budget) so I'm proud of the work the team has done to create streaming STT models with lower word-error rates than OpenAI's largest Whisper model. Admittedly Large v3 is a couple of years old, but we're near the top the HF OpenASR leaderboard, even up against Nvidia's Parakeet family. Anyway, I'd love to get feedback on the models and software, and hear about what people might build with it.
In plain words
Moonshine offers open-weights speech-to-text models that achieve lower word-error rates than OpenAI's Whisper Large v3, built by a six-person startup. The models support streaming transcription and rank near the top of the HF OpenASR leaderboard, competing with Nvidia's Parakeet family. Moonshine includes a software library for effectively deploying these models, designed for developers building speech recognition applications.
written from the facts on this page · September 2026
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