SNAC 24 kHz Codec — GGUF (ggml-quantised)
GGUF / ggml conversion of hubertsiuzdak/snac_24khz — the 24 kHz Multi-Scale Neural Audio Codec used by Orpheus-TTS — for use with CrispStrobe/CrispASR.
SNAC is a small (~25 MB) Residual Vector Quantisation codec by Hubert Siuzdak. Pair it with the cstr/orpheus-3b-0.1-ft-GGUF talker (or any other GGUF orpheus checkpoint) — the talker emits codec tokens but doesn't render audio without this codec.
Files
| File | Type | Size | Notes |
|---|---|---|---|
snac-24khz.gguf | F32 | 25 MB | Full-precision codec — model is small enough that quantisation is not worth the quality risk |
The codec runs in C++ inside libcrispasr once --codec-model snac-24khz.gguf is passed; no Python required at inference time.
Quick start
huggingface-cli download cstr/orpheus-3b-0.1-ft-GGUF orpheus-3b-0.1-ft-q8_0.gguf --local-dir .
huggingface-cli download cstr/snac-24khz-GGUF snac-24khz.gguf --local-dir .
./build/bin/crispasr --backend orpheus \
-m orpheus-3b-0.1-ft-q8_0.gguf \
--codec-model snac-24khz.gguf \
--voice tara --temperature 0.6 \
--tts "Hello, my name is Tara." \
--tts-output hello.wav
Or pass -m auto and CrispASR's auto-download fetches both files from HF.
Architecture
| Component | Details |
|---|---|
| Sample rate | 24 kHz mono |
| Codebooks | 3 (RVQ — 1, 2, 4 entries per super-frame) |
| Codebook size | 4096 (12 bits each) |
| Frame rate | 12 ms (288 samples / hop 512) |
| Super-frame | 7 codec tokens cover 4 codec frames = 32 ms ≈ 768 PCM samples (deinterleave 1+2+4) |
| Decoder | Snake activations + transposed convolutions, full-precision F32 |
The codec maps 7 talker emissions to 1 super-frame; 4 super-frames give a 32 × 32 ms = 128 ms audio chunk (8192 samples at 24 kHz). The streaming protocol from orpheus_snac.py emits the middle 2048 samples of each 4-super-frame sliding window.
Conversion
python models/convert-snac-to-gguf.py \
--input hubertsiuzdak/snac_24khz \
--output snac-24khz.gguf
No quantisation — the model is small enough (~25 MB) that the disk savings would be marginal and the quality risk on the codec output isn't worth it. The Q8_0 path collapses cosine similarity on audio_out below the ASR-roundtrip threshold in our diff harness.
Used by
cstr/orpheus-3b-0.1-ft-GGUF— canonical English Orpheus 3B-FT.- (queued)
cstr/orpheus-kartoffel-de-GGUF— German Kartoffel_Orpheus finetunes. - (queued)
cstr/orpheus-3b-de-q8_0-GGUF— lex-au Orpheus-3B-DE Q8 mirror.
All three reuse this exact codec — only the talker GGUF changes.
Attribution
- Original codec:
hubertsiuzdak/snac_24khz(MIT). Hubert Siuzdak. - Reference paper: SNAC: Multi-Scale Neural Audio Codec.
- Reference codec implementation: hubertsiuzdak/snac.
- GGUF conversion + ggml runtime:
CrispStrobe/CrispASR— seesrc/orpheus_snac.cppandmodels/convert-snac-to-gguf.py.
License
MIT, inherited from the base codec.
Provenance and EU AI Act Art. 53 note
- Upstream model: hubertsiuzdak/snac_24khz — published by
hubertsiuzdak. - Upstream licence:
mit. 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/GGML). 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.
- 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.