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s1-mini-GGUF
by superwhisper · source Hugging Face · updated 2026-08-28
other462 MB~2 GB RAMsource aliveunlabeled
GGUF builds of superwhisper/s1-mini, release v1, for llama.cpp, Ollama, LM Studio, and anything else built on llama.cpp. You can use it in your own dictation app too, just check the license first.
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Source and license
- Source: https://huggingface.co/superwhisper/s1-mini-GGUF
- License: other (custom license: read it at the source before installing)
- Requirements: about 2 GB of RAM, 462 MB on disk (estimate: suggested file size × 1.15 + 0.5 GB; a real measurement comes with lsh models). Runs with llama.cpp, ollama.
- Tags:
ggufasrautomatic-speech-recognitiontext-normalizationinverse-text-normalizationpunctuationtruecasingspeech-to-textdictationpost-processingqwen3llama.cpptext-generationenendpoints_compatibleconversational
Numbers
- 277,684 downloads on Hugging Face
- 41 likes
- license other
- 0.5 GB for s1-mini-q4_k_m.gguf
- 54,249 stars on ggml-org/whisper.cpp
- 352 open issues and PRs
- last release v1.9.5 on 2026-10-06
- 15,664 npm downloads a week for nodejs-whisper
- latest nodejs-whisper@0.3.1
Numbers as of 2026-10-09 19:01 UTC, from the source API.
Summary
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Files
| file | quant | size |
|---|---|---|
s1-mini-f16.gguf | F16 | 1.4 GB |
s1-mini-q4_k_m.gguf | Q4_K_M | 462 MB |
From the source README
S1-mini-GGUF by Superwhisper
GGUF builds of superwhisper/s1-mini,
release v1, for llama.cpp, Ollama, LM Studio, and anything else built on
llama.cpp. You can use it in your own dictation app too, just check the
license first.
S1-mini is a 0.6B-parameter text normalizer for speech-to-text output. It
takes a raw ASR transcript and rewrites it as clean written text: fillers
removed, false starts and self-corrections resolved to the value the speaker
landed on, punctuation and capitalization applied, and spoken numbers, dates,
times, currency and email addresses rendered in written form.
At Q4_K_M it is a 462 MiB file that runs comfortably on a laptop CPU, and on a
held-out set of 7,519 English cases it reaches 94.8% token accuracy.
The model covers English only. It is not a chat model and will not follow
general instructions; it does one job, and you steer it with a control line at
the top of the input. Full documentation lives in the
BF16 repository.
Files
| File | Type | Size | Notes |
|---|---|---|---|
| `s1-mini-q4_k_m.gguf` | Q4_K_M | 462 MB | Recommended. The build the published accuracy was measured on. |
| `s1-mini-f16.gguf` | F16 | 1.4 GB | Unquantized conversion, the intermediate the Q4_K_M is produced from. |
Both files share the same skeleton: architecture `qwen3`, 311 tensors, 28
blocks, a 40,960-token context window, and an embedded chat template. The
Q4_K_M build keeps the most quantization-sensitive tensors at Q6_K (29 of 311)
and the bulk at Q4_K, while normalization parameters stay F32 in both builds.
> [!NOTE]
> The Hub sidebar reports 0.8B parameters for this repo. Qwen3-0.6B sets
> `tie_word_embeddings`, but ships `lm_head.weight…
Source: https://huggingface.co/superwhisper/s1-mini-GGUF
Card id model:hf:superwhisper/s1-mini-GGUF · collected 2026-10-09 19:01 UTC · JSON