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FunAudioLLM/SenseVoiceSmall-GGUF-audiocpp overview

SenseVoiceSmall GGUF for audio.cpp This repository contains a self contained Q8 0 export of SenseVoiceSmall https://huggingface.co/FunAudioLLM/SenseVoiceSmall …

ggufautomatic-speech-recognitionasrsensevoicefunasraudio.cppggmlcpuzhenyuejakolicense:apache-2.0region:us

Runs locally from ~242.4 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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Pipeline
automatic-speech-recognition

Repository Files & Downloads

1 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
sensevoice-small-q8-audiocpp-v1.ggufGGUFQ8242.4 MBDownload

Model Details

Model IDFunAudioLLM/SenseVoiceSmall-GGUF-audiocpp
AuthorFunAudioLLM
Pipelineautomatic-speech-recognition
Licenseapache-2.0
Base model
Last modified2026-08-12T17:52:18.000Z

Model README

---

license: apache-2.0

language:

  • zh
  • en
  • yue
  • ja
  • ko

library_name: gguf

tags:

  • automatic-speech-recognition
  • asr
  • sensevoice
  • funasr
  • audio.cpp
  • gguf
  • ggml
  • cpu

pipeline_tag: automatic-speech-recognition

---

SenseVoiceSmall GGUF for audio.cpp

This repository contains a self-contained Q8_0 export of

SenseVoiceSmall for the

audio.cpp spec-backed runtime. The GGUF

embeds the sense_asr schema-v1 model specification, SenseVoice metadata,

SentencePiece vocabulary, CMVN tensors, and 919 model tensors. It loads

directly without --model-spec-override.

File

| File | Size | SHA256 |

|---|---:|---|

| sensevoice-small-q8-audiocpp-v1.gguf | 254,211,200 bytes | 4dedf169f625437fb336f2959674f399819729a765e184128c0e25a6e16ff0ec |

Usage

audiocpp_cli --task asr --family sense_asr \
  --model sensevoice-small-q8-audiocpp-v1.gguf \
  --backend cpu --audio zh.wav \
  --request-option audio_chunk_mode=none

The integration is tracked in

audio.cpp pull request #218.

Reproducibility

The model was exported from FunAudioLLM/SenseVoiceSmall revision

3847d57b6bdf2dd8875cb1508d2af43d80a16bf7 with the official

runtime/llama.cpp/export_sensevoice_gguf.py exporter using --wtype q8_0

and --model-spec.

On the official 5.616-second Mandarin sample, direct CPU inference produced:

开饭时间早上9点至下午5点。

The text exactly matched the original Q8 model loaded with an external model

specification.

Links

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