Qwen3-TTS 12Hz 0.6B CustomVoice — ONNX
ONNX export of
Qwen/Qwen3-TTS-12Hz-0.6B-CustomVoice
for local inference with ONNX Runtime. Unlike the Base variant, CustomVoice does not
include the ECAPA-TDNN speaker encoder; it uses a set of predefined built-in speaker voices
selected by name at inference time. This is an unofficial community mirror of the ONNX
export; it is not a newly trained model. The Qwen team (Alibaba Cloud) is the original author.
Source
| Field | Value |
|---|
| Upstream model | Qwen/Qwen3-TTS-12Hz-0.6B-CustomVoice |
| Upstream source revision | 85e237c12c027371202489a0ec509ded67b5e4b5 |
| Packaging source revision | 747ac4c3f6c6a317e83f6303148f28585a8bcadf |
| Export tool/script | ONNX export from upstream Qwen3-TTS PyTorch weights (community packaging) |
| Quantization recipe | See onnx/ filenames for FP32/FP16/quant variants shipped in this repo |
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 |
Architecture
- Talker: 28 transformer layers, 16 attn heads, 8 KV heads, hidden=1024
- Code Predictor: 5 layers, generates codebook groups 1-15 from Talker output
- Vocoder: RVQ dequantize -> transformer -> BigVGAN decoder, 12Hz codec -> 24kHz audio
- KV Cache: Decode step uses stacked format (num_layers, B, num_kv_heads, T, head_dim)
Available Speakers
Built-in speaker identities: serena, vivian, uncle_fu, ryan, aiden, ono_anna,
sohee, eric, dylan
Intended Use
Multilingual text-to-speech for local inference via ONNX Runtime, using a predefined voice
profile rather than reference-audio voice cloning. Voice cloning from reference audio
requires the Base variant
tonythethompson/Qwen3-TTS-12Hz-0.6B-Base-ONNX;
the 1.7B CustomVoice variant is in
tonythethompson/Qwen3-TTS-12Hz-1.7B-CustomVoice-ONNX.
Standalone usage (external project)
The snippet below uses an external C# project by elbruno and references that project's ONNX
repo, not this one.
1git clone https://github.com/elbruno/qwen-labs-cs.git
2cd qwen-labs-cs
3python python/download_onnx_models.py --repo-id elbruno/Qwen3-TTS-12Hz-0.6B-CustomVoice-ONNX
4dotnet run --project src/QwenTTS -- --model-dir python/onnx_runtime --text "Hello world" --speaker ryan --language english
Runtime Notes
- Designed for ONNX Runtime compatible runtimes.
- Output sample rate: 24 kHz.
- No reference audio required; select a speaker by name.
- Validate on the target execution provider before production use.
Precision and Packaging
Export tooling, precision, and quantization are recorded in the Source table above. This packaging mirror does not publish independent parity benchmarks; validate on your target execution provider before production use.
Limitations
- Predefined speaker set is fixed; adding new voices requires the Base variant with ECAPA-TDNN voice cloning.
- No repository-specific quality evaluation is documented here.
- Multilingual coverage: verify the upstream model card for supported languages and quality by language.
Safety and Responsible Use
Qwen3-TTS is a voice synthesis model capable of producing realistic speech. CustomVoice uses
predefined speaker identities (not arbitrary voice cloning), which limits some misuse
vectors, but the synthesized output can still be deceptive to listeners.
- Do not create synthetic speech intended to deceive listeners.
- Disclose AI-generated audio where listeners would reasonably expect a human voice.
- Users are responsible for compliance with applicable laws governing synthetic media in their jurisdiction.
License
Apache 2.0 — same as
Qwen/Qwen3-TTS-12Hz-0.6B-CustomVoice. This packaging repo adds no new license terms.
