New Audio APIs for Speech and Transcription

OpenRouter now has two dedicated audio endpoints: /api/v1/audio/speech for text-to-speech and /api/v1/audio/transcriptions for speech-to-text.

These new endpoints deliver specialized models that are generally faster and more cost-efficient than the general audio models we already support, but are more narrowly useful for specific audio tasks.

You can now generate speech from text with OpenAI, Google, or Mistral voices and transcribe audio files with OpenAI Whisper. All with the same routing, billing, and key management you already use for text, video and image generation.

Speech models · Transcription models · Speech docs · Transcription docs

Choosing a model: Audio vs. Speech vs. Transcription

The choice of models is a balance of specialization, cost, and speed. We’ve enabled access to the breadth of options so you can choose the right path for each use case:

	Audio models	Speech models	Transcription models
What it does	Understands audio input and reasons over it, like a voice-native LLM	Converts text into lifelike spoken audio	Converts audio into text
Input → Output	Text/audio → text/audio	Text → audio	Audio → text
Best for	Voice agents, mixed-modality conversations, audio Q&A	Reading text aloud with built-in voices and streaming	Meeting notes, subtitles, feeding voice input into text pipelines
Endpoint	/chat/completions	/audio/speech	/audio/transcriptions
Trade-offs	More powerful but heavier and more expensive	Simpler, faster, cheaper (no reasoning needed)	Purpose-built for accuracy across languages and accents
Browse models	Audio models	Speech models	Transcription models
Docs	Audio output guide	Speech docs	Transcription docs

Try it in the Playground

Both Speech and Transcription have dedicated Playground tabs on model pages (here’s GPT-4o Mini TTS’s Playground and GPT-4o Transcribe’s Playground as examples). For speech models, pick a voice from the dropdown, type your text, and hear the result. For transcription models, drag and drop an audio file and see the transcription.

Each model page also shows quickstart code in Python, TypeScript, curl, and the OpenRouter SDK, so you can copy a working example and have audio running in your app in minutes.

Getting started with Speech models

Send text, get audio back. The response is a raw byte stream you can pipe straight to a file or audio player.

curl https://openrouter.ai/api/v1/audio/speech \
  -H "Authorization: Bearer $OPENROUTER_API_KEY" \
  -H "Content-Type: application/json" \
  --output output.mp3 \
  -d '{
    "model": "openai/gpt-4o-mini-tts-2025-12-15",
    "input": "Hello from OpenRouter.",
    "voice": "alloy",
    "response_format": "mp3"
  }'

Speech providers currently include OpenAI (GPT-4o Mini TTS), Google (Gemini Flash TTS), and Mistral (Voxtral Mini TTS). Each model brings its own voice set, and you can browse available voices on each model’s page. Output comes in MP3 or PCM format.

Provider-specific options pass through cleanly. For example, OpenAI’s speech models accept an instructions field for tone control (e.g., “speak in a warm, friendly tone”).

Getting started with Transcription models

The transcription endpoint takes a base64-encoded audio file and returns text. It supports WAV, MP3, FLAC, and other common formats.

AUDIO_BASE64=$(base64 < recording.wav | tr -d '\n')

curl https://openrouter.ai/api/v1/audio/transcriptions \
  -H "Authorization: Bearer $OPENROUTER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "openai/whisper-large-v3",
    "input_audio": {
      "data": "'"$AUDIO_BASE64"'",
      "format": "wav"
    }
  }'

Transcription providers currently include OpenAI (Whisper, GPT-4o Transcribe, GPT-4o Mini Transcribe), Google (Chirp 3), and Groq (with their fast Whisper inference). You can optionally pass a language hint to improve accuracy for non-English audio.

What’s next

We’re actively adding more providers and voices. If there’s a speech or transcription model you want to see on OpenRouter, tell us on Discord.