---
title: "This 600M Model Fixes What Whisper Leaves Behind"
source_url: https://youtu.be/jp0PGmAwK3w
captured_at: 2026-08-27
author: "Better Stack"
contributor: "ชิดชนก"
platform: youtube
---
# This 600M Model Fixes What Whisper Leaves Behind

youtube video by **Better Stack**, 8m40s, uploaded 2026-08-27. URL: https://youtu.be/jp0PGmAwK3w
Tags: SuperWhisper, SuperWhisper S1, S1-mini, SuperWhisper S1-mini, speech to text, local speech to text, local AI, local AI models, Whisper, whisper.cpp, automatic speech recognition, ASR, ASR post processing, transcript cleanup, text normalization, speech to text AI, offline speech to text, local transcription, AI dictation, local dictation, GGUF, llama.cpp, Ollama, LM Studio, Qwen3

## Shared in LINE Note+
- 2026-08-27 21:40 by ชิดชนก

## Description
SuperWhisper S1-mini is a tiny 600M parameter open model built specifically to clean up messy speech-to-text transcripts completely locally. 

In this video, I test S1-mini on real ASR output with fillers, false starts, self-corrections, spoken numbers, email addresses, technical dictation, and formatting to see how well it turns raw speech into clean text without relying on GPT, Claude, or another cloud LLM.

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Hugging Face - 

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📌 Chapters:
0:00 SuperWhisper S1-mini: Tiny Local Speech-to-Text Cleanup
0:35 What Is S1-mini and How Does It Work?
1:43 Running S1-mini Locally on Mac
2:30 Fixing Fillers, Corrections, Numbers & Emails
3:45 Cleaning Up Messy Speech-to-Text
4:20 Adding S1-mini to a Local ASR Pipeline
5:10 S1-mini vs GPT, Claude & Local LLMs
6:35 S1-mini Pros, Cons & Limitations
7:45 Is S1-mini Worth Using for Developers?
8:25 How to Try SuperWhisper S1-mini