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 Labby Meta·Released 25 September 2024
Llama 3.2 1B Instruct is the smallest Llama text model, meant for summaries, short chats and analysing text in several languages on devices with little computing power. It supports eight core languages and reads about 60 pages at once. Use it for simple, repetitive jobs like tagging or short summaries.
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 | 8,99 DA | 66,90 DA |
per 1M tokens
One company runs this model. OpenDunes sends every request to it. DA per 1M tokens: ↑ what you send · ↓ what comes back.
| Provider | ↑ Sent | ↓ Back | Latency | Throughput | Uptime |
|---|---|---|---|---|---|
| 8,99 DA | 66,90 DA | … | … | … |
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.
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 LabSwap 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="meta-llama/llama-3.2-1b-instruct",
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.
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_biasAbout 0,042 DA per message. ↑ 8,99 DA · ↓ 66,90 DA per 1M tokens.
No. You pay per use from your balance, with no subscription. Try it in Chat at the same price.
Llama 3.2 1B Instruct is the smallest Llama text model, meant for summaries, short chats and analysing text in several languages on devices with little computing power. It supports eight core languages and reads about 60 pages at once. Use it for simple, repetitive jobs like tagging or short summaries.
Llama 3.2 3B Instruct costs 0,031 DA more for the same message.
Deposit dinars with your Edahabia or CIB card. Every model, Llama 3.2 1B Instruct included, is paid from that balance. No foreign card, no conversion.
Meta supports 8 languages: English, German, French, Italian, Portuguese, Hindi, Spanish and Thai. Arabic and Darja are not named.
It reads text. Up to 60K tokens in one request, about 60 pages. It writes up to 41 000 words at once.
Yes, its weights are public. Open weights on Hugging Face
Meta. Released 25 September 2024. It knows the world up to 31 December 2023.
Llama 3.1 8B Instruct is the small model of Meta's Llama 3.1 family, tuned to follow instructions and described as fast and efficient. You send text and get text back; it reads about 131 pages at once and can use tools or fill in an exact form you give it. Use it for sorting, short rewrites, simple chat and high-volume jobs.
Llama 3.3 70B Instruct is a text-only Meta model tuned for conversation in English, Spanish, French, German, Italian, Portuguese, Hindi and Thai. You send a chat, with tools or an exact form to fill in if you need them, and get a reply of up to about 16 pages from a conversation of up to 131 pages. Pick it for assistants and support in those languages.
Llama 4 Scout takes text and pictures and answers in text or code across 12 languages. It reads about 1,300 pages at once, enough to caption or question many images, or take in a very large document in one request. Meta tuned it for chat in many languages, captions and image understanding.
Llama 4 Maverick takes text and pictures and answers in text or code across 12 languages, keeping about a thousand pages of conversation in mind. Meta tuned it for reasoning about images and for assistant-style chat. Use it to answer questions about photos, charts and screenshots, or for multilingual assistants with long conversations.
From what its maker and two benchmark sites publish, and where it stands on OpenDunes. Read 7 Nov 2026.
Thinks first No.
Works through the problem before it answers.
Uses your tools No.
Can call functions your code provides.
Fills your JSON No.
Answers in the JSON shape you give it.
Searches the web No.
Can look things up online while it answers.
Cheaper on repeats No.
A prompt it saw a moment ago costs less the second time.
Open weights
The model's weights are public.
Knows events up to 31 Dec 2023
What it learned stops at this date.
Summarise a customer review in one line
Tag incoming messages by language and topic
Rewrite a short French product description