Turn this customer email into JSON with intent, urgency and order_id.
customer-email.txtMistral Small 3
by MistralReleased 30 January 2025
Mistral Small 3 (2501) is a text model for fast, everyday chat and drafting, released under an open Apache 2.0 licence so you can also run it yourself. It reads about 33 pages at once, answers in text only and cannot use tools here. Mistral reports 81% accuracy on a widely used knowledge test.
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 | 16,64 DA | 26,63 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.
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/mistral-small-24b-instruct-2501",
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_ptop_kmin_pstopseedfrequency_penaltypresence_penaltyrepetition_penaltylogit_biasStructured output
Get JSON you can parse instead of prose.
response_formatstructured_outputsQuestions about Mistral Small 3
How much does Mistral Small 3 cost in dinars?
About 0,030 DA per message. ↑ 16,64 DA · ↓ 26,63 DA per 1M tokens.
Is Mistral Small 3 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 Mistral Small 3 best for?
Mistral Small 3 (2501) is a text model for fast, everyday chat and drafting, released under an open Apache 2.0 licence so you can also run it yourself. It reads about 33 pages at once, answers in text only and cannot use tools here. Mistral reports 81% accuracy on a widely used knowledge test.
Mistral Small 3 or Mistral Small 4?
Mistral Small 4 costs 0,12 DA more for the same message.
How do I pay for Mistral Small 3 without an international card?
Deposit dinars with your Edahabia or CIB card. Every model, Mistral Small 3 included, is paid from that balance. No foreign card, no conversion.
Does Mistral Small 3 work in Arabic, French or Darja?
Mistral's model card tags English, French, German, Spanish, Italian, Portuguese, Chinese, Japanese, Russian and Korean. Arabic and Darja are not named.
Can it read PDFs, images or a whole book?
It reads text. Up to 33K tokens in one request, about 32 pages. It writes up to 12 000 words at once.
Is Mistral Small 3 open source?
Yes, its weights are public. Open weights on Hugging Face
Who makes Mistral Small 3, and when was it released?
Mistral. Released 30 January 2025. It knows the world up to 31 October 2023.
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