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 Amazon·Released 5 December 2024
Amazon Nova Micro 1.0 takes text and gives back text, and it is the quickest to respond in the Nova family, reading up to about 128 pages. Send it text to summarise, translate, sort or brainstorm over, or a quick chat turn; it handles simple maths and basic code. Replies stop at about 5 pages.
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 | 11,65 DA | 46,60 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 |
|---|---|---|---|---|---|
| Amazon BedrockEurope | 11,65 DA | 46,60 DA | … | … | … |
| Amazon Bedrock | 11,65 DA | 46,60 DA | … | … | … |
You pay the price of the provider that served your request. Prices read 15:18 · 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="amazon/nova-micro-v1",
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_kstopTools
Let the model call your functions.
toolsAbout 0,035 DA per message. ↑ 11,65 DA · ↓ 46,60 DA per 1M tokens.
No. You pay per use from your balance, with no subscription. Try it in Chat at the same price.
Amazon Nova Micro 1.0 takes text and gives back text, and it is the quickest to respond in the Nova family, reading up to about 128 pages. Send it text to summarise, translate, sort or brainstorm over, or a quick chat turn; it handles simple maths and basic code. Replies stop at about 5 pages.
Deposit dinars with your Edahabia or CIB card. Every model, Nova Micro 1.0 included, is paid from that balance. No foreign card, no conversion.
Amazon lists English, German, French, Spanish, Italian, Portuguese, Japanese, Hindi and Arabic as generally available, and says the models attempt up to 200 languages. Darja is not named.
It reads text. Up to 128K tokens in one request, about 120 pages. It writes up to 4 000 words at once.
No. Amazon has not published its weights.
Amazon. Released 5 December 2024. It knows the world up to 31 October 2024.
This model takes in plain text of about 8.1 pages at a time and gives back a numeric code for it, not written words. A buyer sits down with it to sort a large pile of articles or reports by subject, or to match a question to the right passage in a long file. Unlike the picture-matching model in its family, it takes in no photos or captions and is built for whole long documents. It stops where a job needs a written reply, since it only produces codes that computers compare, so that kind of work needs a different kind of model.
This model takes a piece of text of up to about eight pages and turns it into a numeric code that computers can compare, so it finds and groups similar writing rather than writing anything itself. Sit down with it to sort thousands of documents by topic, power a search that matches a question to the right passage, or flag near-duplicate text. Unlike its family's picture-matching sibling, which reads only a caption's worth of text, it digests full long documents in one go. It never composes answers or prose, so any job that needs a written reply needs a different kind of model.
This model takes a short piece of text, a picture, or both together, and turns them into a matching code that computers can compare. It reads about a tenth of a page at a time, so it suits short captions, product names, and single photos rather than long documents. Its strength is finding things that are alike: a shopper's words can be matched to product photos, or one picture to similar pictures, because text and images end up in the same shared space. It does not write text or answers, so any job that needs a written reply needs a different kind of model.
Nova 2 Lite reads text, images, video and files, answers in text, can think step by step before replying, and keeps about 1,000 pages in mind at once. Give it documents to pull facts from, video to extract details from, code to write, or a multi-step task that uses the tools you connect to it. Nova Lite 1.0 reads only text and images, about 300 pages, and Nova Premier handles the hardest reasoning.
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
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 No.
Read on docs.aws.amazon.com.
Knows events up to 31 Oct 2024
What it learned stops at this date.
Translate short replies between Arabic and French
Sort support messages by topic
Look up an order through your API
Uses your tools