---
title: How to query audio models
description: Learn how to interact with powerful audio models using Scaleway's Generative APIs service.
tags: generative-apis ai-data audio-models voxtral
dates:
validation: 2025-10-17
posted: 2025-09-22
---
import Requirements from '@macros/iam/requirements.mdx'
Scaleway's Generative APIs service allows users to interact with powerful audio models hosted on the platform.
There are several ways to interact with audio models:
- The Scaleway [console](https://console.scaleway.com) provides a complete [playground](/generative-apis/how-to/query-audio-models/#accessing-the-playground), aiming to test models, adapt parameters, and observe how these changes affect the output in real-time.
- Via the [Chat Completions API](https://www.scaleway.com/en/developers/api/generative-apis/chat-completions) or the [Audio Transcriptions API](https://www.scaleway.com/en/developers/api/generative-apis/#path-audio-create-an-audio-transcription)
- Via your own [dedicated deployment](/generative-apis/how-to/create-deployment/) of a chosen model
- A Scaleway account logged into the [console](https://console.scaleway.com)
- [Owner](/iam/concepts/#owner) status or [IAM permissions](/iam/concepts/#permission) allowing you to perform actions in the intended Organization
- A valid [API key](/iam/how-to/create-api-keys/) for API authentication
- Python 3.7+ installed on your system
## Accessing the playground
Scaleway provides a web playground for instruct-based models hosted on Generative APIs.
1. Navigate to **Generative APIs** under the **AI** section of the [Scaleway console](https://console.scaleway.com/) side menu. The list of models you can query displays.
2. Click the name of the chat model you want to try. Alternatively, click **Try** next to the model's name.
The web playground displays.
## Using the playground
1. Upload an audio file to send to the selected audio model for transcription purposes.
2. Edit the hyperparameters listed on the right column, for example the default temperature for more or less randomness on the outputs.
3. Switch models at the top of the page, to observe the capabilities of chat models offered via Generative APIs.
4. Click **Deploy**, then select the **Serverless** option to get code snippets configured according to your settings in the playground.
You can also choose to deploy a model on your own dedicated Instance by selecting the **Dedicated** option. In this case, you can access the playground after completing the steps in the deployment wizard. Once in the playground of your deployment, click **View code** to get code snippets that match your settings in the playground.
## Querying audio models via API
You can query the models programmatically using your favorite tools or languages.
In the example that follows, we will use the OpenAI Python client.
### Audio Transcriptions API or Chat Completions API?
Both the [Audio Transcriptions API](https://www.scaleway.com/en/developers/api/generative-apis/#path-audio-create-an-audio-transcription) and the [Chat Completions API](https://www.scaleway.com/en/developers/api/generative-apis/chat-completions) are OpenAI-compatible REST APIs that accept audio input.
The **Audio Transcriptions API** is designed for pure speech-to-text (audio transcription) tasks, such as transcribing a voice note or meeting recording file. It can be used with compatible audio models, such as `whisper-large-v3`.
The **Chat Completions API** is more suitable for understanding audio input as part of a broader task, rather than a pure transcription task. For example, building a voice chat assistant which listens and responds in natural language, or sending multiple inputs (audio and text) to be interpreted or classified (answering questions like "Is this audio a ringtone?"). This API can be used for audio tasks with compatible multimodal models, such as `voxtral-small-24b`.
Scaleway's support for the Audio Transcriptions API is currently at beta stage. Support of the full feature set will be incremental.
For full details on these APIs, see the [reference documentation](https://www.scaleway.com/en/developers/api/generative-apis/).
### Installing the OpenAI SDK
Install the OpenAI SDK using pip:
```bash
pip install openai
```
### Initializing the client
Initialize the OpenAI client with your base URL and API key:
In the case of a dedicated Generative APIs deployment, the `base_url` value is the **Public Endpoint URL** displayed on the Overview tab of the deployment's dashboard.
```python
from openai import OpenAI
# Initialize the client with your base URL and API key
client = OpenAI(
base_url="https://api.scaleway.ai/v1", # Scaleway's Generative APIs service URL
api_key="" # Your unique API secret key from Scaleway
)
```
### Transcribing audio
You can now generate a text transcription of a given audio file using a suitable API / model combination of your choice.
The Audio Transcriptions API expects audio files to be found locally. It does not support passing the URL of a remote audio file.
In the example below, a local audio file [scaleway-ai-revolution.mp3](https://genapi-documentation-assets.s3.fr-par.scw.cloud/scaleway-ai-revolution.mp3) is sent to the model. The resulting text transcription is printed to the screen.
```python
MODEL = "openai/whisper-large-v3:fp16"
AUDIO = 'scaleway-ai-revolution.mp3'
audio_file = open(AUDIO, "rb")
response = client.audio.transcriptions.create(
model=MODEL,
file=audio_file,
language='en'
)
print(response.text)
```
See the [dedicated API documentation](https://www.scaleway.com/en/developers/api/generative-apis/#path-audio-create-an-audio-transcription) for a full list of all available parameters.
#### Transcribing a remote audio file
In the example below, an audio file from a remote URL (`https://genapi-documentation-assets.s3.fr-par.scw.cloud/scaleway-ai-revolution.mp3`) is downloaded using the `requests` library, base64-encoded, and then sent to the model in a chat completion request alongside a transcription prompt. The resulting text transcription is printed to the screen.
```python
import base64
import requests
MODEL = "voxtral-small-24b-2507"
url = "https://genapi-documentation-assets.s3.fr-par.scw.cloud/scaleway-ai-revolution.mp3"
response = requests.get(url)
audio_data = response.content
encoded_string = base64.b64encode(audio_data).decode("utf-8")
content = [
{
"role": "user",
"content": [
{
"type": "text",
"text": "Transcribe this audio"
},
{
"type": "input_audio",
"input_audio": {
"data": encoded_string,
"format": "mp3"
}
}
]
}
]
response = client.chat.completions.create(
model=MODEL,
messages=content,
temperature=0.2, # Adjusts creativity
max_tokens=2048, # Limits the length of the output
top_p=0.95 # Controls diversity through nucleus sampling. You usually only need to use temperature.
)
print(response.choices[0].message.content)
```
See the [dedicated API documentation](https://www.scaleway.com/en/developers/api/generative-apis/#path-chat-completions-create-an) for a full list of all available parameters.
#### Transcribing a local audio file
In the example below, a local audio file [scaleway-ai-revolution.mp3](https://genapi-documentation-assets.s3.fr-par.scw.cloud/scaleway-ai-revolution.mp3) is base-64 encoded and sent to the model, alongside a transcription prompt. The resulting text transcription is printed to the screen.
```python
import base64
MODEL = "voxtral-small-24b-2507"
with open('scaleway-ai-revolution.mp3', 'rb') as raw_file:
audio_data = raw_file.read()
encoded_string = base64.b64encode(audio_data).decode("utf-8")
content = [
{
"role": "user",
"content": [
{
"type": "text",
"text": "Transcribe this audio"
},
{
"type": "input_audio",
"input_audio": {
"data": encoded_string,
"format": "mp3"
}
}
]
}
]
response = client.chat.completions.create(
model=MODEL,
messages=content,
temperature=0.2, # Adjusts creativity
max_tokens=2048, # Limits the length of the output
top_p=0.95 # Controls diversity through nucleus sampling. You usually only need to use temperature.
)
print(response.choices[0].message.content)
```
Various parameters such as `temperature` and `max_tokens` control the output. See the [dedicated API documentation](https://www.scaleway.com/en/developers/api/generative-apis/chat-completions) for a full list of all available parameters.