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AI 模型库/canberkkkkkk/ema-lightning
MODEL PROFILE · 模型档案

ema-lightning

canberkkkkkk · ema-lightning

**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

译文排队中，当前展示来源原文。

语音合成license:apache-2.0
上下文窗口来源未披露
输入 → 输出文本 → 音频
模型权重待核验
档案更新时间2026/10/30 04:27:54
OVERVIEW

模型介绍

**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

主要特点

特点摘要待依据来源补齐，不凭模型名称推断能力。

局限与注意事项

暂无足够来源支持具体缺点结论。请重点验证实际任务表现、时延、数据政策、许可与版本生命周期。

PRICING & COST

来源报价与费用分析

同一模型在不同渠道、地区和配置下可能采用不同价格。下表独立保留各渠道报价，不将渠道价格视为厂商官方统一价格。

来源 / 渠道输入输出计费单位采集时间
暂未取得可核验报价，请查阅来源渠道。

按月估算基础 Token 费用

—

预估不包含缓存优惠、阶梯定价、多模态附加费用、网络检索、税费及推理额外输出。

INDEPENDENT BENCHMARKS

公开评测与运行配置

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。

查看完整已收录榜单 →

常见问题

开放权重是否代表可以免费商用？

不一定。应核对具体版本许可证、商用门槛和使用政策。自部署还会产生算力和维护成本。

这些价格是实时结算价格吗？

不是实时结算价格，而是带采集时间的来源报价快照。请到对应渠道核对当前版本、区域、折扣和计费方式。

资料来源与可追溯记录

huggingface · canberkkkkkk/ema-lightning ↗2026/10/30 04:27:54
huggingface · enrich:25056111-7a8e-4954-8312-a0b0c78c6ae2 ↗2026/10/29 08:40:23

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。