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VyvoTTS-v0-Qwen3-0.6B is an English Text-to-Speech (TTS) model built on the Qwen3-0.6B architecture and trained using a 10,000-hour dataset to produce natural-sounding speech. With approximately 810 million parameters and licensed under MIT, the model offers flexible usage as a pretrained base for further development, especially recommended to be enhanced by leveraging the Emilia dataset and fine-tuning for single-speaker scenarios. Users can integrate VyvoTTS with the unsloth and SNAC frameworks for speech generation, and the model supports sequence lengths up to 8,192 tokens. Although it currently exhibits a high Word Error Rate (WER), its open-source nature and compatibility with popular Python libraries make it an accessible starting point for advanced speech synthesis projects.
| File Name | Size | Quant Type |
|---|---|---|
| VyvoTTS-v0-Qwen3-0.6B.BF16.gguf | 1.26 GB | BF16 |
| VyvoTTS-v0-Qwen3-0.6B.F16.gguf | 1.26 GB | F16 |
| VyvoTTS-v0-Qwen3-0.6B.F32.gguf | 2.51 GB | F32 |
| VyvoTTS-v0-Qwen3-0.6B.Q2_K.gguf | 321 MB | Q2_K |
| VyvoTTS-v0-Qwen3-0.6B.Q3_K_L.gguf | 393 MB | Q3_K_L |
| VyvoTTS-v0-Qwen3-0.6B.Q3_K_M.gguf | 372 MB | Q3_K_M |
| VyvoTTS-v0-Qwen3-0.6B.Q3_K_S.gguf | 348 MB | Q3_K_S |
| VyvoTTS-v0-Qwen3-0.6B.Q4_0.gguf | 406 MB | Q4_0 |
| VyvoTTS-v0-Qwen3-0.6B.Q4_1.gguf | 434 MB | Q4_1 |
| VyvoTTS-v0-Qwen3-0.6B.Q4_K.gguf | 421 MB | Q4_K |
| VyvoTTS-v0-Qwen3-0.6B.Q4_K_M.gguf | 421 MB | Q4_K_M |
| VyvoTTS-v0-Qwen3-0.6B.Q4_K_S.gguf | 408 MB | Q4_K_S |
| VyvoTTS-v0-Qwen3-0.6B.Q5_0.gguf | 461 MB | Q5_0 |
| VyvoTTS-v0-Qwen3-0.6B.Q5_1.gguf | 489 MB | Q5_1 |
| VyvoTTS-v0-Qwen3-0.6B.Q5_K.gguf | 469 MB | Q5_K |
| VyvoTTS-v0-Qwen3-0.6B.Q5_K_M.gguf | 469 MB | Q5_K_M |
| VyvoTTS-v0-Qwen3-0.6B.Q5_K_S.gguf | 461 MB | Q5_K_S |
| VyvoTTS-v0-Qwen3-0.6B.Q6_K.gguf | 520 MB | Q6_K |
| VyvoTTS-v0-Qwen3-0.6B.Q8_0.gguf | 671 MB | Q8_0 |
