OmniVoice β single-file ComfyUI checkpoints
Single-file checkpoints of k2-fsa/OmniVoice (Qwen3 LLM + HiggsAudioV2 codec), repacked for ComfyUI-OmniVoice-Native. Config, codec config, and BPE tokenizer are embedded as safetensors metadata β no sidecar files needed.
Files
omnivoice.safetensors(3.3GB, full quality) β most robust, recommended for tags + voice-design prompts.omnivoice-int8.safetensors(1.1GB, INT8-ConvRot) β same quality on plain prompts, smaller download. ~86% top-1 agreement with full.
Use
- Install the pack: ComfyUI Manager β search
OmniVoice, orgit clone https://github.com/Aero-Ex/ComfyUI-OmniVoiceintoComfyUI/custom_nodes/. Nopip installneeded. - Put a file from this repo into
ComfyUI/models/omnivoice/. Load OmniVoice ModelβOmniVoice Generate. For a designed voice, addOmniVoice Voice Designβinstruct.
Defaults: 32 steps, guidance 2.0, 25 tok/s. num_steps 16 roughly halves generation time. Texts over ~30s are auto-split into ~15s chunks and cross-faded.
Notes
Voice clone:
ref_audio+ref_text(transcript required, no ASR). One voice per Generate call β multi-speaker dialogue = one Generate per speaker, then concat.Voice design: gender, age, pitch, whisper, English accent / Chinese dialect via the
instructstring.Vocalization tags (exact spelling, spoken by the model):
[laughter],[sigh],[question-en],[question-ah],[question-oh],[question-ei],[question-yi],[confirmation-en],[surprise-ah],[surprise-oh],[surprise-wa],[surprise-yo],[dissatisfaction-hnn].Wait, what [surprise-ah]? You finished it already [question-oh]? Ha [laughter]! I knew you could do it [confirmation-en]. Phew [sigh], now we can finally rest.Keep normal punctuation spacing around tags (
! Ha,. Phew, never!Ha). Crushed punctuation derails takes, especially on INT8.Same seed can give different takes across checkpoints β test seeds 1β3 per setup and pin the keeper.
No output post-processing β use standard ComfyUI audio nodes for gain/fades/trim.
Credit / license
Model: k2-fsa OmniVoice. This repo only repacks the weights into single-file ComfyUI checkpoints; see the upstream repo and paper for training details.