by MistralReleased 13 August 2026
Mistral's 3B Voxtral Mini for speech and audio understanding, handling transcription, translation and compact audio processing; Voxtral Small does the same work with 24B parameters
You pay for what each request uses. No subscription, no minimum.
One minute of audio, the ordinary use
Every rate
| Meter | ↑ you send | ↓ comes back |
|---|---|---|
| Second of audio | 0,0055 DA |
per second of audio sent
One company runs this model. OpenDunes sends every request to it.
You pay the price of the provider that served your request. Prices read 15:20 · speed over the last 30 minutes · uptime over 3 days.
Swap the base URL and the key. Your OpenAI code runs unchanged.
import os
from openai import OpenAI
client = OpenAI(
base_url="https://opendunes.com/v1",
api_key=os.environ["OPENDUNES_API_KEY"],
)
with open("meeting.mp3", "rb") as f:
resp = client.audio.transcriptions.create(model="mistralai/voxtral-mini-3b-2507", file=f)
print(resp.text)Runs this request once on your balance.
About 0,33 DA per minute of audio. ↑ 0,0055 DA per second of audio.
No. You pay per use from your balance, with no subscription. Try it in Chat at the same price.
Mistral's 3B Voxtral Mini for speech and audio understanding, handling transcription, translation and compact audio processing; Voxtral Small does the same work with 24B parameters.
Deposit dinars with your Edahabia or CIB card. Every model, Voxtral Mini 3B 2507 included, is paid from that balance. No foreign card, no conversion.
Mistral names English, Spanish, French, Portuguese, Hindi, German, Dutch and Italian. Arabic and Darja are not named.
Speaker labels: not stated. Word timings: not stated.
Up to 25 MB as an upload. Longer audio goes in the request body.
Mistral. Released 13 August 2026.
Mistral's flagship speech-to-text model that turns audio into transcripts with word timestamps and speaker labels, with context biasing for domain-specific vocabulary
The Voxtral Mini derivative that only transcribes, taking audio from meetings, voice notes and podcasts and returning the text through a standard transcription request
Mistral's compact speech-to-text model that turns audio into transcripts with word timestamps and speaker labels, and can be steered with context biasing to catch domain terms
Mistral AI's text embedding model from late 2023, whose 1024-dimension vectors capture how passages relate, for semantic search and RAG; Codestral Embed is the version for code
From what its maker and two benchmark sites publish, and where it stands on OpenDunes. Read 7 Nov 2026.
Transcribe voice notes from customers
Audio
Turn a short interview into text
Transcribe recordings without saying which language they are in