TontaubeV1 - Open TTS model release for local long-form generation

Hey everyone,

I am the co-founder of Tontaube. My brother and I just released TontaubeV1, a 2.9B-parameter open-weight TTS model focused on expressive speech, long-form generation, and low-latency local inference.

The model is primarily aimed at English and German and supports zero-shot voice cloning from up to one minute of reference audio.

Some technical details:

- Four separate autoregressive models generate the codec streams from coarse semantic structure to acoustic detail

- The models become progressively smaller for the higher codebooks

- Character-level text tokenization

- Shared logical positions between aligned text and audio

- Streaming and effectively unbounded long-form generation through a rolling context window

- vLLM-based inference with batching across requests and acoustic stages

On a warmed RTX 5090, we measured:

- Around 0.08 RTF for a single text

- As low as 0.02 RTF with batching, or roughly 50× real time

- Around 200 ms to first encoded audio in the streaming path

The current release requires a GPU with at least 24 GB of VRAM for the low-VRAM and balanced profiles, or 32 GB for the high-throughput profile. The reason it takes up so much VRAM right now is the vllm implementation, which allows for high-concurrency and low-latency serving. We plan to release quantized versions aimed at smaller GPUs and on-device use, as well as fine-tuning support.

We also ran a 400-passage LLM-as-a-judge audiobook benchmark. On prosody, TontaubeV1 scored 50.1% against ElevenLabs Flash v2.5 and was preferred over Fish Audio S2 Pro, Gradium, and Cartesia Sonic 3. The methodology, caveats, and confidence intervals are described in the report.

We know that human listening tests remain the gold standard. We were not able to conduct a large-scale human study before release, but we plan to test TontaubeV1 with real listeners through TTS Arena V2 and the Artificial Analysis Text to Speech Arena in the coming days.

Links:

- Weights: https://huggingface.co/TontaubeAI/TontaubeV1

- Inference code: https://github.com/craitech/tontaube

- Technical report: https://tontaube.ai/papers/tontaube-v1-technical-report.pdf

- Samples/playground: https://tontaube.ai/playground or without login first at https://tontaube.ai

I’d be very interested in independent installation experiences, VRAM measurements on other GPUs, and any weird failure cases you find. Please let me know where I can help!