Artificial Intelligence · 20.08.2026, 22:31 UTC
Meet S1-mini: Superwhisper’s 462 MB Open-Weights Text Normalizer That Turns Raw ASR Transcripts Into Clean Written Text
| Schweregrad | info |
|---|---|
| Kategorie | Artificial Intelligence |
| Quelle | MarkTechPost ↗ |
| Veröffentlicht | 20.08.2026 UTC |
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Superwhisper has released the S1 family of models: S1-Voice, S1-Language, and S1-mini. S1-Voice is a cloud speech-to-text model, and S1-Language is a cloud instruction-following model for cleanup and formatting. The one that is quite interesting outside the app is S1-mini, released with open weights on Hugging Face. S1-mini is a 0.6B text normalizer, not a transcriber and not a chat model. It sits after automatic speech recognition and rewrites raw transcripts as clean written text: fillers removed, self-corrections resolved to what the speaker landed on, punctuation and capitalization applied, and spoken numbers, dates, currency, and email addresses rendered in written form. It is fine-tuned from Qwen/Qwen3-0.6B, covers English only in release v1, and is steered entirely by a three-axis control line placed above the transcript. Superwhisper reports 94.8% token accuracy on a held-out set of 7,519 cases, measured greedy on the quantized build.
Is it deployable?
Yes, but only S1-mini. S1-mini is published on Hugging Face under Apache 2.0 plus a naming clause. S1-Voice and S1-Language are Superwhisper-hosted services, so they are consumable, not self-hostable.
Company level: Any level. The Q4_K_M GGUF build is a 462 MB file that runs on a laptop CPU. Solo developers can ship it inside a desktop app. Enterprises can run it behind a VPC where audio transcripts cannot leave the network.
Industries: Healthcare and clinical documentation, legal, financial services, customer support, developer tooling, accessibility and live captioning.
Applications: Dictation apps, …