OmniVoice GGUF
GGUF weights for omnivoice.cpp, a C++17/GGML port of OmniVoice (k2-fsa/OmniVoice). Multilingual zero shot TTS, 646 languages, 24 kHz mono. Runs on CPU, CUDA, ROCm, Metal, Vulkan.
Files
Two GGUFs load together :
omnivoice-base-{variant}.gguf Qwen3 0.6B backbone, text -> tokens omnivoice-tokenizer-{variant}.gguf HuBERT + DAC + RVQ, tokens <-> 24 kHz audio
| variant | base | tokenizer | use case |
|---|---|---|---|
| F32 | 2.46 GB | 734 MB | reference, debug, conversion |
| BF16 | 1.23 GB | 373 MB | source faithful, max precision |
| Q8_0 | 656 MB | 289 MB | recommended default |
| Q4_K_M | 407 MB | 252 MB | lowest VRAM |
Quick start
git clone --recurse-submodules https://github.com/ServeurpersoCom/omnivoice.cpp.git
cd omnivoice.cpp && ./buildcuda.sh
mkdir -p models
huggingface-cli download Serveurperso/OmniVoice-GGUF \
omnivoice-base-Q8_0.gguf omnivoice-tokenizer-Q8_0.gguf \
--local-dir models
cd examples
./tts.sh # voice design -> tts.wav
./clone.sh # voice cloning -> clone.wav
Backends
Set GGML_BACKEND to force a device, otherwise the runtime picks the
best one available.
| value | target |
|---|---|
CUDA0 | NVIDIA GPU, fastest path on Ada / Blackwell |
Vulkan0 | Cross vendor GPU (AMD / Intel / NVIDIA) |
Metal | Apple Silicon GPU |
CPU | CPU fallback, x86 variant auto selected |
Quantization policy
Tokenizer GGUFs are not uniform quants. Three categories get a dedicated treatment :
| tensor | dtype across all variants |
|---|---|
| RVQ codebooks, fc, fc2, project_in / project_out | F32 |
| Snake activation alpha | F32 |
| Conv kernels with non alignable rows (K=7,3,1) | F16 (in Q* variants) |
Same fallback as llama.cpp tensor_type_fallback : F16 has no block
size and matches the runtime target dtype on every backend. The base
LM (Qwen3 0.6B, hidden = 1024) has all dimensions divisible by 256 so
the fallback never triggers, the LM follows standard llama.cpp K-quant
across variants.
License
Upstream weights : OmniVoice by Xiaomi / k2-fsa, CC-BY-NC 4.0 Upstream code : OmniVoice by Xiaomi / k2-fsa, Apache 2.0 Audio codec : Higgs Audio v2 (bosonai/higgs-audio-v2-tokenizer), Apache 2.0 GGUF tooling : omnivoice.cpp, MIT
The upstream code is Apache 2.0 but the pre-trained weights are CC-BY-NC because of constraints from the training data. These GGUF files are conversions of those weights and carry the same non commercial terms.