ElevenLabs: Eleven v4 Turbo

Eleven v4 Turbo is a text-to-speech model from ElevenLabs, the company known for its voice synthesis work. It sits in the speech category and is positioned as a low-latency variant of Eleven v4, keeping the expressive delivery and audio tags of that model while being tuned for faster generation. If you are building anything that needs to turn written text into spoken audio, this is the kind of model you would evaluate first.

The model takes text as its only input and produces speech as its only output. It supports more than 90 languages, so you are not restricted to English source text. A set of named voices is available: george, sarah, adam, alice, bella, bill, brian, callum, charlie, chris, daniel, eric, harry, jessica, laura, liam, lily, matilda, river, roger and will. Audio tags are supported, which means you can influence the delivery of the generated speech rather than getting a flat read. No context length is published for this model, and no request parameters are listed as supported, so plan around the text you send rather than around a documented token budget.

The practical uses follow directly from fast text-to-speech with expressive control. Voiceovers for video or narrated content, where you want a consistent named voice across a long script. Accessibility features that read articles, documents or interface text aloud. Conversational agents and assistants that need to reply with audio quickly enough to feel responsive. Localisation work, since the 90+ language support lets one pipeline serve multiple markets with the same model. Audio tags are useful when a script needs emphasis, pauses or a particular tone rather than a neutral reading.

You call it through api14's OpenAI-compatible API using the model id "elevenlabs/eleven-v4-turbo". Because the interface follows the OpenAI format, you can point an existing OpenAI client at api14 and change the model id, rather than writing a provider-specific integration. Send your text as the input and select one of the listed voices. Note that no additional request parameters are documented as supported for this model, so keep requests to the basics the endpoint accepts.

One thing to weigh is scope. This model only produces speech from text; it does not accept audio input, generate text, or handle images, so transcription, translation and reasoning tasks belong with other models. There is also no published context length, which makes it a poor fit if you need to reason about how much text fits in a single request. For long scripts, chunking your input is the safer approach. If your workload is latency-sensitive speech synthesis in one of the supported languages, this model is a reasonable default to test.