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Qwen3 TTS 12Hz 0.6B Base ONNX

ONNX export of Qwen/Qwen3-TTS-12Hz-0.6B-Base for local inference with ONNX Runtime. Includes an ECAPA-TDNN speaker encoder for voice cloning from 3 seconds of reference audio. This is an unofficial community mirror...

ArtAudio modelBasismodellQwen/Qwen3-TTS-12Hz-0.6B-BaseVersionRevision 59ab2d7Verleger@tonythethompsonCBewertung

Modellquelle

Art
Audio model, Embedding
Dateigröße
403 KB–420 MB
Basismodell
Qwen/Qwen3-TTS-12Hz-0.6B-Base
Version
vRevision 59ab2d7
Aktualisiert
3. Okt. 2026
Downloads
0
Parameter
6B
Aufgaben
Audio
Quelle
Hugging Face

Quellenbeschreibung

Qwen3-TTS 12Hz 0.6B Base — ONNX

ONNX export of Qwen/Qwen3-TTS-12Hz-0.6B-Base for local inference with ONNX Runtime. Includes an ECAPA-TDNN speaker encoder for voice cloning from ~3 seconds of reference audio. 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

FieldValue
Upstream modelQwen/Qwen3-TTS-12Hz-0.6B-Base
Upstream source revision5d83992436eae1d760afd27aff78a71d676296fc
Packaging source revision17a2fccf89a5391005f9ff163b07e13f7814dddf
Export tool/scriptONNX export from upstream Qwen3-TTS PyTorch weights (community packaging)
Quantization recipeSee onnx/ filenames for FP32/FP16/quant variants shipped in this repo

Files

FileDescriptionSize
speaker_encoder.onnx + .dataECAPA-TDNN speaker encoder~34 MB
talker_prefill.onnx + .dataTalker LM prefill (28 layers)~1.7 GB
talker_decode.onnx + .dataTalker LM single-step decode~1.7 GB
code_predictor.onnxCode Predictor (5 layers, 15 groups)~440 MB
vocoder.onnxVocoder decoder (24kHz output)~2.7 MB
embeddings/Text/codec embeddings as .npy + config~1.4 GB
tokenizer/BPE tokenizer (vocab.json, merges.txt)~4 MB

Architecture

  • Speaker Encoder: ECAPA-TDNN, 128 mel bins input, 1024-dim speaker embedding output
  • 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

Intended Use

Multilingual text-to-speech for local inference via ONNX Runtime. The Base variant synthesizes speech conditioned on a speaker embedding extracted from a short reference clip, enabling voice-consistent synthesis. The 1.7B Base variant is in tonythethompson/Qwen3-TTS-12Hz-1.7B-Base-ONNX; predefined-speaker variants are in the CustomVoice repos.

Standalone usage (external project)

The snippet below uses the external ElBruno/QwenTTS C# wrapper and references that project's ONNX repo, not this one. It is included only as a reference for standalone C# use.

dotnet add package ElBruno.QwenTTS.VoiceCloning
using ElBruno.QwenTTS.VoiceCloning.Pipeline;

var cloner = await VoiceClonePipeline.CreateAsync();
await cloner.SynthesizeAsync("Hello world!", "reference.wav", "output.wav", "english");

Runtime Notes

  • Designed for ONNX Runtime compatible runtimes.
  • Output sample rate: 24 kHz.
  • Voice cloning reference: ~3 seconds of reference audio recommended.
  • 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

  • Voice cloning quality depends on reference audio quality; noisy or very short clips may degrade results.
  • Multilingual capability: verify the upstream model card for supported languages and quality by language.
  • No repository-specific audio quality evaluation is documented here.

Safety and Responsible Use

Qwen3-TTS is a voice synthesis and voice cloning model capable of producing realistic speech closely matching a target speaker.

  • Do not use to impersonate real individuals without their explicit consent.
  • Do not generate synthetic speech intended to deceive listeners about a speaker's identity.
  • Disclose AI-generated audio where listeners would reasonably expect a human voice.
  • Users are responsible for compliance with applicable laws governing synthetic media and voice cloning in their jurisdiction.

License

Apache 2.0 — same as Qwen/Qwen3-TTS-12Hz-0.6B-Base. This packaging repo adds no new license terms.

Quellen

1 Quelle
Hugging FacePrimärVersion 59ab2d796c653e97f94f2350d215b266888fcd94
huggingface.co/tonythethompson/Qwen3-TTS-12Hz-0.6B-Base-ONNX/tree/59ab2d796c653e97f94f2350d215b266888fcd94

Verifiziert 3. Okt.

Modellartefakte

6 Artefakte

code_predictor.onnx

onnx · 420 MB · SHA-256 44c528d01c09…faad · Hugging Face

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speaker_encoder.onnx

onnx · 403 KB · SHA-256 c5fd5fce0938…a48c · Hugging Face

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talker_decode.onnx

onnx · 4,54 MB · SHA-256 082ef0c7d195…6424 · Hugging Face

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talker_prefill.onnx

onnx · 4,41 MB · SHA-256 79975996d51e…bc05 · Hugging Face

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tokenizer12hz_encode.onnx

onnx · 1.003 KB · SHA-256 6ea63a991d94…b7ab · Hugging Face

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vocoder.onnx

onnx · 2,59 MB · SHA-256 bea75666aeb6…2225 · Hugging Face

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Quellenauszüge

3 Auszüge

--- license: apache-2.0 base_model: Qwen/Qwen3-TTS-12Hz-0.6B-Base base_model_relation: quantized pipeline_tag: text-to-speech library_name: onnxruntime language: - multilingual tags: - onnx - onnxruntime - tts - qwen3-tts - text-to-speech - voice-cloning - ecapa-tdnn --- # Qwen3-TTS 12Hz 0.6B Base — ONNX ONNX export of [Qwen/Qwen3-TTS-12Hz-0.6B-Base](https://huggingface.co/Qwen/Qwen3-TTS-12Hz-0.6B-Base) for local inference with ONNX Runtime. Includes an ECAPA-TDNN speaker encoder for voice cloning from ~3 seconds of reference audio. 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-Base](https://huggingface.co/Qwen/Qwen3-TTS-12Hz-0.6B-Base) | | Upstream source revision | `5d83992436eae1d760afd27aff78a71d676296fc` | | Packaging source revision | `17a2fccf89a5391005f9ff163b07e13f7814dddf` | | 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 | |---|---|---:| | `speaker_encoder.onnx` + `.data` | ECAPA-TDNN speaker encoder | ~34 MB | | `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) | ~440 MB | | `vocoder.onnx` | Vocoder decoder (24kHz output) | ~2.7 MB | | `embeddings/` | Text/codec embeddings as .npy + config | ~1.4 GB | | `tokenizer/` | BPE tokenizer (vocab.json, merges.txt) | ~4 MB | ## Architecture - **Speaker Encoder**: ECAPA-TDNN, 128 mel bins input, 1024-dim speaker embedding output - **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 ## Intended Use Multilingual text-to-speech for local inference via ONNX Runtime. The Base variant synthesizes speech conditioned on a speaker embedding extracted from a short reference clip, enabling voice-consistent synthesis. The 1.7B Base variant is in [`tony...

Source context: 0 downloads · 0 likes · Pipeline text-to-speech · Library onnxruntime · Repo tonythethompson/Qwen3-TTS-12Hz-0.6B-Base-ONNX

Source context: 0 downloads · 0 likes · Pipeline text-to-speech · Library onnxruntime · Repo tonythethompson/Qwen3-TTS-12Hz-0.6B-Base-ONNX