FreyaTTS-small

FreyaTTS-small is a 183M-parameter Turkish text-to-speech model, and the open-source member of the FreyaTTS family. It is tokenizer-free at the character level (92 symbols, no phonemizer or G2P) and generates speech with a non-autoregressive conditional flow-matching DiT in the frozen AudioVAE2 latent space (25 Hz, 64-dim latents, 16 kHz encode / 48 kHz decode). Output is 48 kHz mono.

• Repository: https://github.com/freyavoiceai/FreyaTTS
• Eval set: https://huggingface.co/datasets/freyavoice/freya-tr-eval
• License: Apache-2.0

The FreyaTTS family

FreyaTTS-small (this model) is our compact, Apache-2.0, self-hostable model, released in full: weights, inference code, and training pipeline.

FreyaTTS-large is our production model, serving Turkish voice agents at Freya (YC S25) with higher naturalness and expressivity. It is available commercially rather than as open weights. For access, contact us at dev@freyavoice.ai.

The model id freyavoice/freya-tts predates this naming and is unchanged; it refers to FreyaTTS-small.

Usage

from freyatts import FreyaTTS

tts = FreyaTTS.from_pretrained("freyavoice/freya-tts", device="cuda")
wav = tts.synthesize("Merhaba, size nasıl yardımcı olabilirim?")   # np.float32, 48 kHz
tts.save_wav(wav, "output.wav")

Clone freyavoiceai/FreyaTTS and install requirements.txt.

Model details

• Architecture: conditional flow-matching diffusion transformer, non-autoregressive, 32-step Euler ODE, no CFG
• Parameters: 183.2M
• Input: character-level Turkish, 92-symbol vocabulary
• Latent space: frozen AudioVAE2 (Apache-2.0, openbmb/VoxCPM2), 64-dim at 25 Hz, decodes to 48 kHz
• Training: from scratch on Turkish speech; pretraining followed by SFT stage 1/2 (voice lock, short-utterance coverage)
• Voice: single target speaker, no cloning

Evaluation

On Freya-TR-Eval: WER 8.0% / CER 3.0%, ranking 3rd of 7 among open sub-1B Turkish TTS models, ahead of XTTS-v2 (11.1% WER) and F5-TTS (24.3% WER).

Speed

• RTX 4090: RTF 0.10-0.11, TTFT ~0.5 s, 1.5 GB VRAM, 9.4 audio-s/s at concurrency 4
• About 3.2x faster RTF and 3.7x less VRAM than the 2B VoxCPM2
• Apple M3 laptop CPU: RTF 0.70 (fp32); ~0.12 end to end via Core ML on Apple silicon

Citation

FreyaTTS-small is described in our technical report, arXiv:2607.09530:

@misc{pamuk2026freyattscompacttokenizerfreeflowmatching,
      title={FreyaTTS: A Compact Tokenizer-Free Flow-Matching Transformer for Turkish-First Speech Synthesis}, 
      author={Ahmet Erdem Pamuk and Ömer Yentür and Ahmet Tunga Bayrak and Yavuz Alp Sencer Öztürk and Mustafa Yavuz},
      year={2026},
      eprint={2607.09530},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2607.09530}, 
}