Model reference · open weights
s1-mini is an open-weight language model from superwhisper, listed in the AxForge catalogue. AxForge can bring it up on EU-owned hardware for you on request — with the licence handled where one is required.
About
S1-mini by Superwhisper [](https://superwhisper.com) [](https://discord.gg/tF98XvJNvB) [](https://huggingface.co/superwhisper/s1-mini/tree/v1) 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. On a held-out set of 7,519 English cases it reaches 94.8% token accuracy, and the quantized build is a 462 MiB file that runs comfortably on a laptop CPU. This is release v1, and it covers English only. S1-mini 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. Fine-tuned from Qwen/Qwen3-0.6B. If you want to run it in llama.cpp, Ollama, LM Studio, or anything else built on llama.cpp, grab the GGUF builds from superwhisper/s1-mini-GGUF. You can use it in your own dictation app too, just check the license first. Releases are tagged, so you can pin one: frompretrained("superwhisper/s1-mini", revision="v1"). Model overview [!NOTE] The Hub sidebar reports 0.8B parameters for this repo. config.json sets tiewordembeddings, but model.safetensors still stores lmhead.weight as a materialized copy of the input embedding, so the 155.6M-parameter embedding is counted twice: 751.6M tensor elements against 596.0M unique parameters. The layout is inherited from Qwen/Qwen3-0.6B, which reports 0.8B on the Hub for the same reason. The table above counts unique parameters. Input. The model expects the system prompt, then a control line, a newline, and one raw ASR transcript, which will usually arrive lowercase and unpunctuated. That is the shape it was trained on. Output. It returns the cleaned transcript as plain text and nothing else, with no preamble and no explanation. Under Structure: lists the output may contain Markdown bullets, and under Context: email it may contain blank lines separating a greeting, body and sign-off. When the input is nothing but filler or noise, the correct output is an empty s
Summarised from the published model card. Read the full card on the HuggingFace links below.
Specifications
| Maker | superwhisper |
|---|---|
| Type | Language models |
| Parameters (lead) | 752M |
| Context | 40k tokens |
| Variants | 1 |
| Runs with | transformers |
| Based on | Qwen/Qwen3-0.6B |
| Released | 2026-08-12 |
| Popularity | 6k downloads / month |
| Likes | 307 |
| Licence | Commercial licence needed |
How it works
Variants
Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.
| Variant | Params | Precision | VRAM | Fits 16 GB | Weights |
|---|---|---|---|---|---|
| s1-mini | 752M | BF16 | ~1.7 GB | ✓ | Weights ↗ |
Using it via the API
Once AxForge deploys s1-mini for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (s1-mini below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/chat/completions \
-H "Authorization: Bearer $AXFORGE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"s1-mini","messages":[{"role":"user","content":"Hello"}]}'
Licence
The weights are open but its licence needs a commercial agreement for business use. AxForge can arrange that licence and host the model for you — you pay AxForge, we settle with the model’s maker. Ask us for a quote. Read the licence ↗