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
Mistral Medium 3.5 (batch)
by MistralReleased 30 April 2026
Mistral Medium 3.5 is a large model taking text, pictures and files and answering in text. It is the Medium line's pick for automated work: it uses several tools in a row reliably, stays on long tasks, and lets you set thinking effort per request. Its picture reading copes with any size or shape of image, and you can download it to run yourself.
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 | 249,63 DA | 1 248,13 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 15:19 · speed over the last 30 minutes · uptime over 3 days.
Call 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-medium-3-5:batch",
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_penaltyReasoning
Let it think before answering — and see the thinking.
reasoningreasoning_effortinclude_reasoningStructured output
Get JSON you can parse instead of prose.
response_formatstructured_outputsTools
Let the model call your functions.
toolstool_choiceQuestions about Mistral Medium 3.5 (batch)
How much does Mistral Medium 3.5 (batch) cost in dinars?
About 0,87 DA per message. ↑ 249,63 DA · ↓ 1 248,13 DA per 1M tokens.
Is Mistral Medium 3.5 (batch) free? Can I try it?
No. You pay per use from your balance, with no subscription. Run it once from Call it in code, at the same price.
What is Mistral Medium 3.5 (batch) best for?
Mistral Medium 3.5 is a large model taking text, pictures and files and answering in text. It is the Medium line's pick for automated work: it uses several tools in a row reliably, stays on long tasks, and lets you set thinking effort per request. Its picture reading copes with any size or shape of image, and you can download it to run yourself.
How do I pay for Mistral Medium 3.5 (batch) without an international card?
Deposit dinars with your Edahabia or CIB card. Every model, Mistral Medium 3.5 (batch) included, is paid from that balance. No foreign card, no conversion.
Does Mistral Medium 3.5 (batch) work in Arabic, French or Darja?
Mistral says it supports dozens of languages, naming French and Arabic among them. Darja is not named.
Can it read PDFs, images or a whole book?
It reads text, images and PDFs. Up to 262K tokens in one request, about 260 pages. It writes up to 157 000 words at once.
Is Mistral Medium 3.5 (batch) open source?
Yes, its weights are public.
Who makes Mistral Medium 3.5 (batch), and when was it released?
Mistral. Released 30 April 2026.
Other Mistral models, priced in dinars
See all Mistral modelsThe 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