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AI model by OpenAI

GPT-4o mini TTS for business

OpenAI's current text-to-speech model for turning text into natural spoken audio, at a low price level.

  • Reviewed on September 24, 2026
  • OpenAI

Capability tiersRelative, not benchmarks

Reasoning Very low
Coding Very low
Vision Very low
Speed High
Price level Low
Context size Very low
Tool calling Very low
Structured output Very low

Key facts about GPT-4o mini TTS

Model ID at review
gpt-4o-mini-tts
Provider
OpenAI
Main category
Speech
Open weights
No, available as a hosted service
Last reviewed
September 24, 2026

Fit

Where it fits and where it does not

Good at

  • Spoken replies in voice assistants.

  • Audio versions of articles and messages.

  • Accessibility features in apps.

  • Low-cost speech at volume.

  • Simple integration through the same API as other OpenAI models.

Not the right choice for

  • Cloning a specific person's voice.

  • Very long texts in one request, given the 2,000 token input limit.

  • Transcription, which needs a speech-to-text model.

  • Pretending an AI voice is a real person.

Use cases

Business use cases we would use it for

Voice assistants

Spoken replies for phone and app assistants. See voice AI.

Audio content

Audio versions of help articles, updates and lessons.

Accessibility

Read-aloud features for users who prefer listening.

Our notes

When we would choose it

gpt-4o-mini-tts is OpenAI's current text-to-speech model at the time of review, with a default snapshot from December 2025. It turns text of up to 2,000 tokens into spoken audio. The older tts-1 and tts-1-hd models are still listed without a deprecation notice.

For many business uses, a low-cost, natural-sounding voice is all that is needed: reading a reply aloud in an app, voicing a phone assistant or producing audio versions of help content. For voice cloning, many languages or very expressive speech, a specialist such as ElevenLabs may fit better.

In a voice assistant, text-to-speech is one link in a chain: speech-to-text, a language model, then speech again. The total delay matters more than any single step. We measure it end to end on real calls, and we keep responses short so speech can start quickly.

Whatever voice you use, tell callers and listeners that they are hearing an AI voice. It is honest, it sets expectations and in many places it is required. See voice AI and AI customer support.

Finally, test the voice with the people who will hear it. A short listening session with a few customers or staff often reveals problems with pace, pronunciation of names or tone that no metric will catch.

Before you commit

Things to check before you commit

  • Input limit

    The input limit is 2,000 tokens, so long texts must be split.

  • Voice fit

    Listen to the available voices with your own scripts and brand tone.

  • Disclosure

    Tell listeners when a voice is AI-generated.

  • Latency

    For live calls, measure the full delay from text to first audio.

Alternatives

Models to compare it with

ElevenLabs Eleven v3

ElevenLabs text-to-speech: the expressive Eleven v3 in 70+ languages, a real-time conversational version, and the low-latency Flash models, with voice cloning.

GPT Transcribe

OpenAI's current speech-to-text model, replacing Whisper and the GPT-4o transcribe models, with streaming and keyword or language hints.

Deepgram Nova-3 and Flux

Deepgram's speech-to-text models: Nova-3 for general transcription in 60+ languages, and Flux for voice agents with built-in end-of-turn detection.

Keep exploring

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Questions people ask us

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