Model overview
**Tiny, fast and accurate Turkish text to speech.** A 5.6M-parameter DiT acoustic model and a 3M-parameter vocoder: 8.6M in total, about 34 MB. Apache 2.0. - **Most accurate on Freya-TR-Eval:** 0.92% WER, the lowest of every system measured, including ElevenLabs v4, Gemini 3.8 and the 2.38B-parameter Trendyol-TTS. - **Fast:** first audio in 3.86 ms and 440× faster than real time on an RTX 4090; 1,316× with batching. - **Streams:** audio starts while the rest of the text is still being generated. - **Cheap:** about $0.0085 per million characters on a rented RTX 4090. - **Runs anywhere:** GPU or CPU, fully offline. No API key, and no text or audio leaves the machine. - **One model serves many callers:** call it from as many threads as you like; its scheduler, Playhead, runs everyone's work together on the GPU. - **Code:** [EMA Lightning on GitHub][github] - **Package:** `pip install ema-lightning` - **Text frontend:** normalizer-tr, by Erdem Tuna
Key features
特点摘要待依据来源补齐，不凭模型名称推断能力。
Limitations & considerations
Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.
Source prices & cost analysis
Prices vary by channel, region and configuration. Channel quotes are listed independently and are not treated as a single official provider price.
| Source / channel | Input | Output | Billing unit | Collected at |
|---|---|---|---|---|
| No verified prices yet. Check the source channel. | ||||
Estimate monthly base token costs
Estimates exclude cache discounts, tiered pricing, multimodal surcharges, web search, taxes and additional reasoning output.
Public benchmarks & run configuration
暂无已采集的可核验公开评分。模型未上榜不代表能力较低。
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Sources & traceability
许可证：apache-2.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。