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Fun ASR Nano 2512 GGUF

GGUF conversions of FunAudioLLM/Fun-ASR-Nano-2512 for use with transcribe.cpp.

KindOtherBase modelFunAudioLLM/Fun-ASR-Nano-2512VersionRevision e653a5bCgrade

Model source

Kind
Other
File size
850 MB
Base model
FunAudioLLM/Fun-ASR-Nano-2512
Version
vRevision e653a5b
Updated
Sep 27, 2026
Downloads
17
Source
Hugging Face

Source excerpt

GGUF conversions of FunAudioLLM/Fun-ASR-Nano-2512 for use with transcribe.cpp.

Sources

1 source
Hugging FacePrimaryVersion e653a5b1c8380dbaf91f680369e2a450d9f97408
huggingface.co/memoravox/Fun-ASR-Nano-2512-gguf/tree/e653a5b1c8380dbaf91f680369e2a450d9f97408

Verified Aug 30

Model artifacts

1 artifact

Fun-ASR-Nano-2512-Q8_0.gguf

gguf · 850 MB · SHA-256 681caef6df15…9e61 · Hugging Face

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Source excerpts

2 excerpts

--- license: other base_model: FunAudioLLM/Fun-ASR-Nano-2512 base_model_relation: quantized library_name: transcribe.cpp pipeline_tag: automatic-speech-recognition language: - zh - en - ja tags: - gguf - transcribe.cpp - asr - speech-to-text - fun-asr-nano - sense-voice-encoder - qwen3 - audio-llm transcribe_cpp: wer_librispeech_test_clean: bf16: 1.78 f16: 1.79 q8_0: 1.79 q6_k: 1.78 q5_k_m: 1.82 q4_k_m: 1.92 rtf_m4_max: metal: 77.5 cpu: 27 rtf_ryzen_4750u: vulkan: 10.5 cpu: 6.5 streaming: false translate: false lang_detect: false timestamps: none --- # Fun-ASR-Nano-2512: transcribe.cpp GGUF GGUF conversions of [FunAudioLLM/Fun-ASR-Nano-2512](https://huggingface.co/FunAudioLLM/Fun-ASR-Nano-2512) for use with [transcribe.cpp](https://github.com/handy-computer/transcribe.cpp). Ported from upstream commit [a7088d620f755dcdca575b63db184c3ad55b2865](https://huggingface.co/FunAudioLLM/Fun-ASR-Nano-2512/commit/a7088d620f755dcdca575b63db184c3ad55b2865), pinned 2026-05-06. Validated against the FunASR reference at transcribe.cpp commit [f094d28](https://github.com/handy-computer/transcribe.cpp/tree/f094d28) on 2026-05-06. Offline speech-to-text in Chinese, English, and Japanese, plus 7 Chinese dialects (Wu, Cantonese, Min, Hakka, Gan, Xiang, Jin) and 26 regional Mandarin accents. ~800M trainable parameters wrapping a frozen SenseVoiceEncoderSmall (50 SAN-M main blocks + 20 transformer blocks), a 2-layer audio adaptor (512 → 1024), and a bundled Qwen3-0.6B LLM (28 layers, 16/8 GQA, BF16) that produces the transcript autoregressively. Takes a 16 kHz mono WAV and emits text. Not a streaming model, no translation, no built-in long-form chunking, no timestamps. ITN (inverse text normalization) is supported by the model and exposed via the `--itn` CLI flag and `transcribe_funasr_nano_params { use_itn }` in the library API. ## Downloads | Quantization | Download | Size | WER (LibriSpeech test-clean) | | --- | --- | ---: | ---: | | BF16 | [Fun-ASR-Nano-2512-BF16.gguf](https://huggingface.co/handy-computer/Fun-ASR-Nano-2512-gguf/resolve/main/Fun-ASR-Nano-2512-BF16.gguf) | 1590 MB | 1.78% | | F16 | [Fun-ASR-Nano-2512-F16.gguf](https://huggingface.co/handy-computer/Fun-ASR-Nano-2512-gguf/resolve/main/Fun-ASR-Nano-2512-F16.gguf) | 1590 MB | 1.79% | | Q8_0 | [Fun-ASR-Nano-2512-Q8_0.gguf](https://huggingface.co/handy-computer/Fun-ASR-Nano-2512-g...

Source context: 17 downloads · 0 likes · Pipeline automatic-speech-recognition · Library transcribe.cpp · Repo memoravox/Fun-ASR-Nano-2512-gguf