ElevenLabs: Eleven Turbo v2.5

Eleven Turbo v2.5 is a text-to-speech model from ElevenLabs, listed on api14 under the speech category. It is made by ElevenLabs and is identified on the platform by the model id elevenlabs/eleven-turbo-v2.5. It sits in the Turbo line, which is positioned around low latency, so it is aimed at developers who need speech generated quickly rather than at offline batch rendering where speed does not matter.

The model takes text as its only input and produces speech as its only output. It supports 32 languages, which makes it a reasonable choice when your application serves users who are not English speakers, and the provider describes it as balancing quality and speed for developer use cases that need non-English languages. It ships with a set of named voices: george, sarah, adam, alice, bella, bill, brian, callum, charlie, chris, daniel, eric, harry, jessica, laura, liam, lily, matilda, river, roger and will. The provider description mentions a 40,000-character limit on input, so long passages need to be split before they are sent. No context length in tokens is published for this model, and no request parameters are listed as supported.

The practical uses follow from text in, speech out, with low latency and broad language coverage. You would reach for it when building voice output into an application: reading responses aloud in an assistant, generating narration or audio versions of written content, producing prompts and announcements for interactive voice systems, or creating spoken versions of material for users who prefer listening. The named voice list means you can pick a consistent voice per product, per locale or per persona without training anything yourself. Because the input is capped by character count, it suits utterances, paragraphs and short scripts more than entire books in a single request.

You call it through api14's OpenAI-compatible API using the model id elevenlabs/eleven-turbo-v2.5, so existing OpenAI client libraries and request shapes work with the platform's base URL. The model accepts text input and returns speech output. No request parameters are listed as supported for this model, so plan on sending the text and the model id, and check the live documentation for how voice selection is passed before you build around a specific parameter. The page shows a live price table, so consult that for current rates rather than relying on anything written here.

There are a couple of cases where another model may fit better. If your workload is English only and you do not need the non-English coverage, a different speech model may be a closer match. If you need token-based context handling or a wide set of tunable request parameters, this model does not advertise them, and a model with a published context length and a fuller parameter list would be easier to integrate. The 40,000-character input limit also means very long documents must be chunked and stitched together on your side.