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PulpCut/Qwen3-TTS-12Hz-0.6B-Base-safetensors
Qwen3-TTS-12Hz-0.6B-Base-safetensors is a text-to-speech model from PulpCut. Use it when you need text read aloud. The card lists the license as apache-2.0.
Qwen3-TTS 12Hz 0.6B Base split into one safetensors file per subsystem, so a C engine can map each on its own and validate them separately. The weights are not retrained, merged, pruned or quantized. If you want the m…
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Updated Aug 21, 2026
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From the Hugging Face model README
Qwen3-TTS 12Hz 0.6B Base split into one safetensors file per subsystem, so a C engine can map each on its own and validate them separately. The weights are not retrained, merged, pruned or quantized. If you want the model itself, use the original; this exists so H3ddle can load it without a Python runtime.
| file | what it holds |
|---|---|
talker.safetensors | 28 layers at 1024 wide, plus the 151936 × 2048 text embedding |
code_predictor.safetensors | the 5-layer model that emits code groups 1–15 |
speaker_encoder.safetensors | ECAPA-TDNN over a 128-band mel |
codec_decoder.safetensors | RVQ, an 8-layer transformer, and the vocoder |
tokenizer.json | the vocabulary, byte for byte the released one |
The release is two checkpoints holding five subsystems between them. Four are needed to speak. Two transforms alter any values, and both are exact or a division the reference performs anyway:
embedding_sum / max(cluster_usage, 1e-5) — which is the division the reference does on every
decode. Reading embedding_sum raw and skipping this yields noise that sounds
like a subtle decoder bug.Everything else is copied byte for byte. The talker keeps its released bfloat16 and the codec decoder its released float32.
encoder.* from the speech tokenizer — a Mimi codec encoder that turns a
reference clip into codes for in-context cloning. H3ddle clones from the ECAPA
speaker embedding instead, so the encoder is 31 unused quantizers and a
convolution stack that would otherwise have to be ported and shipped.
If you need in-context cloning, this package cannot do it. Use the original.
These are runtime gains from H3ddle's native Metal execution of the same package; the checkpoint itself is not a speed-distilled model.
| comparison | regular / baseline | optimized path | resulting gain |
|---|---|---|---|
| talker + code predictor, six-second utterance | 8.48 s CPU | 3.66 s Metal | 56.8% (2.32x) |
| codec decode, 79 frames | 8.02 s CPU | 1.22 s Metal | 84.8% (6.57x) |
| complete 79-frame utterance after codec move | 13.20 s | 4.90 s | 62.9% (2.69x) |
The CPU and Metal codec outputs agree within normal F32 accumulation error; both speech paths were listened to and judged correct. Actual time varies with utterance length, sampling, reference audio, and Mac.
Apache 2.0, from the original. NOTICE records the attribution and the
modifications above; LICENSE is the licence text.
Qwen3-TTS is by Alibaba Cloud.