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elbruno/
Qwen3-TTS-12Hz-0.6B-CustomVoice-ONNX

Name: Qwen3-TTS-12Hz-0.6B-CustomVoice-ONNX
Availability: InStock

Qwen/Qwen3-TTS-12Hz-0.6B-CustomVoice

quantized

apache-2.0

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Qwen3-TTS 12Hz 0.6B CustomVoice — ONNX

ONNX export of Qwen/Qwen3-TTS-12Hz-0.6B-CustomVoice for local inference with C# / ONNX Runtime.

Files

File	Description	Size
`talker_prefill.onnx` + `.data`	Talker LM prefill (28 layers)	~1.7 GB
`talker_decode.onnx` + `.data`	Talker LM single-step decode	~1.7 GB
`code_predictor.onnx`	Code Predictor (5 layers, 15 groups)	~420 MB
`vocoder.onnx` + `.data`	Vocoder decoder (24kHz output)	~437 MB
`embeddings/`	Text/codec embeddings as .npy + config	~1.4 GB
`tokenizer/`	BPE tokenizer (vocab.json, merges.txt)	~4 MB

Usage with C#

bash

# Clone the app repo
git clone https://github.com/elbruno/qwen-labs-cs.git
cd qwen-labs-cs

# Download models
python python/download_onnx_models.py --repo-id elbruno/Qwen3-TTS-12Hz-0.6B-CustomVoice-ONNX

# Run
dotnet run --project src/QwenTTS -- --model-dir python/onnx_runtime --text "Hello world" --speaker ryan --language english

Architecture

Talker: 28 transformer layers, 16 attn heads, 8 KV heads, hidden=1024
Code Predictor: 5 layers, generates codebook groups 1-15
Vocoder: RVQ dequantize → transformer → BigVGAN decoder, 12Hz → 24kHz (1920× upsample)
KV Cache: Decode uses stacked format (num_layers, B, num_kv_heads, T, head_dim)
Speakers: serena, vivian, uncle_fu, ryan, aiden, ono_anna, sohee, eric, dylan

License

Apache-2.0 (same as base model)