OpenAI-Compatible Speech to Text API

Transcribe audio through Eden AI’s OpenAI-compatible transcriptions endpoint. Point any OpenAI client at https://api.edenai.run/v3 and client.audio.transcriptions works as a drop-in replacement for OpenAI’s speech to text.

Overview

Method	Path	Purpose
`POST`	`/v3/audio/transcriptions`	Transcribe an audio file. Returns the transcript as JSON
`GET`	`/v3/audio/transcriptions/models`	Transcription models available in your region, as `provider/model` ids

The call is synchronous: the transcript comes back in the response, with Eden’s cost (USD) and provider fields added.

Transcription models are only available on /v3/audio/transcriptions. They are not in GET /v3/models, which lists chat models.

This is different from Expert Model speech to text, an asynchronous job API through /v3/universal-ai/async that covers more providers (Amazon, AssemblyAI, Gladia, Google, Microsoft and others) and options such as speaker diarization. Use /v3/audio/transcriptions when you want an OpenAI-compatible, drop-in transcription surface.

Models

Provider	Model string
Groq	`groq/whisper-large-v3`, `groq/whisper-large-v3-turbo`
Deepgram	`deepgram/nova-3`, `deepgram/nova-2`, `deepgram/whisper-large`
Mistral	`mistral/voxtral-mini-latest`

Call GET /v3/audio/transcriptions/models for the full list available in your region, with the per-second price of each model.

Transcribing a file

The endpoint takes the audio in one of two ways, chosen by the request’s Content-Type:

multipart/form-data: the audio is uploaded as a file part. This is what the OpenAI SDK sends.
application/json: the audio is referenced by file_url (an https:// URL or a data:audio/...;base64,... URL) or by file_id (a file uploaded to Eden AI through File Upload). Set exactly one of the two.

Uploading the file

The official OpenAI SDK works unchanged once base_url points at Eden AI:

from openai import OpenAI

client = OpenAI(base_url="https://api.edenai.run/v3", api_key="YOUR_API_KEY")

with open("recording.wav", "rb") as audio_file:
    transcript = client.audio.transcriptions.create(
        model="groq/whisper-large-v3-turbo",
        file=audio_file,
    )

print(transcript.text)
# Eden AI's extra fields are on the same object
print(transcript.model_extra.get("provider"), transcript.model_extra.get("cost"))

curl -X POST https://api.edenai.run/v3/audio/transcriptions \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -F model="groq/whisper-large-v3-turbo" \
  -F file="@recording.wav"

Referencing a URL

import requests

url = "https://api.edenai.run/v3/audio/transcriptions"
headers = {
    "Authorization": "Bearer YOUR_API_KEY",
    "Content-Type": "application/json",
}

payload = {
    "model": "groq/whisper-large-v3-turbo",
    "file_url": "https://raw.githubusercontent.com/openai/whisper/main/tests/jfk.flac",
    "language": "en",
}

response = requests.post(url, headers=headers, json=payload)
result = response.json()

print(result["text"])
print("Provider:", result["provider"], "| Cost (USD):", result.get("cost"))

curl -X POST https://api.edenai.run/v3/audio/transcriptions \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "groq/whisper-large-v3-turbo",
    "file_url": "https://raw.githubusercontent.com/openai/whisper/main/tests/jfk.flac",
    "language": "en"
  }'

Request parameters

Field	Required	Description
`model`	yes	`provider/model`, e.g. `groq/whisper-large-v3-turbo`. The model name alone (`whisper-large-v3-turbo`) also works, through Provider Routing
`file`	one of three	The audio file, as a multipart upload
`file_url`	one of three	JSON only. An `https://` URL or a `data:audio/...;base64,...` URL
`file_id`	one of three	JSON only. The id of a file uploaded to Eden AI
`language`	no	ISO-639-1 code of the spoken language, e.g. `en`. Omit it to let the model detect the language
`prompt`	no	Text that guides the model’s style or continues the context of a previous segment
`response_format`	no	`json` (default) or `verbose_json`. See Response format
`timestamp_granularities`	no	`["segment"]` and/or `["word"]`, with `verbose_json`. Honored by the models that support it
`temperature`	no	Sampling temperature between 0 and 1

Unknown fields are ignored. The audio can be at most 25 MB.

Response format

{
  "text": "And so, my fellow Americans, ask not what your country can do for you, ask what you can do for your country.",
  "usage": null,
  "cost": 0.00012221,
  "provider": "groq"
}

With "response_format": "verbose_json", the response also carries the detected language, the audio duration in seconds, and segments with start and end times. Models that support word timestamps add words when timestamp_granularities includes "word".

Use json or verbose_json. Unlike OpenAI, text, srt and vtt do not return a plain-text or subtitle body. The Groq and Deepgram models ignore them and return the JSON transcript; other models may return an error. With the OpenAI SDK, keep the default json format: passing response_format="text" makes the SDK return the raw JSON string instead of a Transcription object.

Listing transcription models

cURL

curl https://api.edenai.run/v3/audio/transcriptions/models \
  -H "Authorization: Bearer YOUR_API_KEY"

Each entry carries its pricing, e.g. {"input_cost_per_second": 0.00001111} for groq/whisper-large-v3-turbo. The endpoint takes the same view parameter as the other model listings.

Pricing

Transcription is billed per second of audio, at the rate GET /v3/audio/transcriptions/models shows: an 11-second clip on groq/whisper-large-v3-turbo costs 11 ×

0.00001111 ≈

0.000122. The amount charged is in the response’s cost field.

Limitations

Files up to 25 MB. A larger file returns 413. A file whose duration cannot be read returns 400.
No @edenai routing. "model": "@edenai" returns 400; name a model.
No fallbacks. The field is ignored, like any unknown field: only model is tried, and a failure is not retried on another model.
No streaming. The transcript is returned in one response once the whole file is transcribed.
No translations endpoint. /v3/audio/translations (speech to English text) is not implemented.

V3 Documentation

Quick Start

Overview

LLMs

Expert Models

General

Organization

Data Governance

Integrations

OpenAI-Compatible Speech to Text API

Overview

Models

Transcribing a file

Uploading the file

Referencing a URL

Request parameters

Response format

Listing transcription models

Pricing

Limitations

Next Steps

Text to Speech

Expert Speech to Text

​Overview

​Models

​Transcribing a file

​Uploading the file

​Referencing a URL

​Request parameters

​Response format

​Listing transcription models

​Pricing

​Limitations

​Next Steps

Text to Speech

Expert Speech to Text

Overview

Models

Transcribing a file

Uploading the file

Referencing a URL

Request parameters

Response format

Listing transcription models

Pricing

Limitations

Next Steps