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FluidInference/qwen3-tts-coreml
qwen3-tts-coreml is a text-to-speech model from FluidInference. Use it when you need text read aloud. It is set up for coremltools. The card lists the license as apache-2.0.
CoreML conversion of Qwen/Qwen3-TTS (0.6B) for on-device inference on Apple platforms.
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From the Hugging Face model README
CoreML conversion of Qwen/Qwen3-TTS (0.6B) for on-device inference on Apple platforms.
Supports English and Chinese text-to-speech synthesis.
| Model | Description | Size |
|---|---|---|
qwen3_tts_lm_prefill_v9 | LM KV-cache prefill (text + speaker conditioning) | ~2.8 GB |
qwen3_tts_lm_decode_v10 | Autoregressive LM decode (CB0 codec token generation) | ~1.8 GB |
qwen3_tts_cp_prefill | Code predictor prefill (CB1-15 conditioning) | ~432 MB |
qwen3_tts_cp_decode | Code predictor decode (CB1-15 generation) | ~420 MB |
qwen3_tts_decoder_10s | Audio decoder (16-codebook codes → 24kHz waveform) | ~436 MB |
speaker_embedding_official.npy | Default speaker embedding (1024-dim) | 4 KB |
Total: ~5.9 GB
Text tokens + Speaker embedding
↓
LM Prefill (KV cache initialization)
↓
LM Decode (CB0 codec tokens, temperature=0.9, top_k=50)
↓
Code Predictor Prefill + Decode (CB1-15 per frame)
↓
Audio Decoder (16 codebooks → 24kHz waveform)
↓
Silence trimming → Final audio
import FluidAudioTTS
let manager = Qwen3TtsManager()
try await manager.loadFromDirectory(modelDir)
let wav = try await manager.synthesize(
text: "Hello world",
tokenIds: [9707, 1879, ...], // Pre-tokenized with Qwen3 processor
useSpeaker: true
)
See FluidAudio for the full Swift framework.
Converted using coremltools from the original PyTorch weights. Conversion scripts are in the mobius repository.
Apache-2.0, inherited from Qwen/Qwen3-TTS.