---

license: apache-2.0

base_model: bosonai/higgs-audio-v3-stt

tags:

• automatic-speech-recognition
• gguf
• crispasr
• whisper
• qwen3

library_name: gguf

pipeline_tag: automatic-speech-recognition

language:

• en

---

higgs-audio-v3-stt — GGUF

GGUF conversions of bosonai/higgs-audio-v3-stt

for CrispASR.

higgs-audio-v3-stt is a speech-to-text model: a **Whisper-large-v3 audio

encoder → depthwise-temporal-conv projector → Qwen3-1.7B decoder**. A

<|AUDIO|> placeholder in a ChatML prompt is replaced by the projected audio

embeddings and the LLM autoregressively decodes the transcript.

Files

| File | Quant | Size | Notes |

|------|-------|------|-------|

| higgs-stt-f16.gguf | F16 | 5.0 GB | full precision |

| higgs-stt-q8_0.gguf | Q8_0 | 3.2 GB | near-lossless; recommended |

| higgs-stt-q4_k.gguf | Q4_K | 2.3 GB | smallest; transcribes verbatim on test clips |

All three transcribe the canonical JFK clip and a 45 s multi-chunk clip

verbatim, matching the bf16 reference. The tied input/output embeddings

(token_embd.weight / output.weight, the lm_head) are kept at F16 in every

quant — quantizing them perturbs every logit.

Usage (CrispASR)

# auto-download:
crispasr -m auto --backend higgs-stt audio.wav
# or an explicit file:
crispasr -m higgs-stt-q8_0.gguf --backend higgs-stt audio.wav

Architecture note (chunked encoder)

higgs-audio does not encode audio as a single padded 30 s Whisper window.

It splits the waveform into chunk_size_seconds (4 s) chunks, encodes **each

chunk independently** (chunk-local positional embeddings, within-chunk

attention) through the Whisper tower + projector, then concatenates the

per-chunk audio embeddings. The decoder then attends over the whole concatenated

sequence in a single pass, so long audio is handled without cross-chunk context

loss. Encoding one global window instead corrupts the conditioning (every valid

frame attends to the silence padding) and derails the decoder. This is the key

detail for any reimplementation.

License

Apache-2.0, inherited from the base model

bosonai/higgs-audio-v3-stt.

Provenance and EU AI Act Art. 53 note

• Upstream model: bosonai/higgs-audio-v3-stt — published by bosonai.
• Upstream licence: apache-2.0. This repository redistributes under the same terms; it grants no rights the upstream licence does not.
• What was done here: format conversion and/or quantisation only (GGUF). No training, no fine-tuning, no merging, no distillation, no change to architecture, vocabulary or capability. Only the numeric representation of the upstream weights differs.
• Training data: documented — where it is documented at all — by the upstream provider; see the upstream model card. No training data was used, added or selected by this repository. No training-content summary was found on the upstream model card at the time of writing; that documentation gap is upstream's and is not filled here.
• Provider status: under Regulation (EU) 2024/1689 the upstream authors remain the provider of this model. Converting the serialisation format does not make this repository the provider of a new general-purpose AI model, and no such claim is made. Questions about training content, copyright policy or model capability belong upstream.