Turn this customer email into JSON with intent, urgency and order_id.
customer-email.txtVoxtral Small 24B 2507
by MistralReleased 30 October 2025
Voxtral Small, Mistral Small 3 with audio input added and its text performance kept, so one model with tool calls can transcribe, translate and understand speech as well as read and write text
What it costs
You pay for what each request uses. No subscription, no minimum.
One message, the ordinary use
Every rate
| Meter | ↑ you send | ↓ comes back |
|---|---|---|
| Text tokens | 33,28 DA | 99,85 DA |
| Cached tokens read | 3,33 DA | |
| Audio tokens | 33 283,56 DA |
per 1M tokens
- When you pay
- After the answer, from your balance. Nothing is held.
- Why it varies
- A longer question or a longer answer costs more.
- After each one
- The exact charge shows on the request.
Where your request runs
One company runs this model. OpenDunes sends every request to it. DA per 1M tokens: ↑ what you send · ↓ what comes back.
Also charged: audio ↑ 33 283,56 DA per 1M audio tokens.
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.
See it in action
Real requests, real replies. Try any of them yourself — one click, pre-filled.
Two lines to welcome a shop in Oran.
Welcome to our new shop in Oran — fresh bread every morning, and coffee the way the city likes it. Come in, the first cup is on us.
Try in Chat LabTry your own request — same model, pre-selected.
Open Chat LabCall it in code
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"],
)
resp = client.chat.completions.create(
model="mistralai/voxtral-small-24b-2507",
messages=[{"role": "user", "content": "Two lines to welcome a shop in Oran."}],
)
print(resp.choices[0].message.content)Runs this request once on your balance.
Parameters you can send
Standard OpenAI fields, grouped by what they control. Anything not listed is accepted and ignored.
Shaping the reply
How long, how varied, where to stop.
max_tokenstemperaturetop_pstopseedfrequency_penaltypresence_penaltyStructured output
Get JSON you can parse instead of prose.
response_formatstructured_outputsTools
Let the model call your functions.
toolstool_choiceQuestions about Voxtral Small 24B 2507
How much does Voxtral Small 24B 2507 cost in dinars?
About 0,083 DA per message. ↑ 33,28 DA · ↓ 99,85 DA per 1M tokens.
Is Voxtral Small 24B 2507 free? Can I try it?
No. You pay per use from your balance, with no subscription. Try it in Chat at the same price.
What is Voxtral Small 24B 2507 best for?
Voxtral Small, Mistral Small 3 with audio input added and its text performance kept, so one model with tool calls can transcribe, translate and understand speech as well as read and write text.
How do I pay for Voxtral Small 24B 2507 without an international card?
Deposit dinars with your Edahabia or CIB card. Every model, Voxtral Small 24B 2507 included, is paid from that balance. No foreign card, no conversion.
Does Voxtral Small 24B 2507 work in Arabic, French or Darja?
Mistral names English, Spanish, French, Portuguese, Hindi, German, Dutch and Italian. Arabic and Darja are not named.
Can it read PDFs, images or a whole book?
It reads text, audio and PDFs. Up to 33K tokens in one request, about 32 pages. It writes up to 20 000 words at once.
Is Voxtral Small 24B 2507 open source?
Yes, its weights are public. Open weights on Hugging Face
Who makes Voxtral Small 24B 2507, and when was it released?
Mistral. Released 30 October 2025.
Other Mistral models, priced in dinars
See all Mistral modelsMistral'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