by CohereReleased 29 October 2026
This model accepts text and pictures as input and outputs numerical representations of the content. It can process up to 120 pages of material at once and generate up to 110 pages of output. It is designed to be a higher accuracy tier within its family of models. This model is limited to processing and outputting these representations and cannot perform tasks requiring complex reasoning.
You pay for what each request uses. No subscription, no minimum.
One page, the ordinary use
Every rate
| Meter | ↑ you send | ↓ comes back |
|---|---|---|
| Text tokens | 39,94 DA |
per 1M tokens
One company runs this model. OpenDunes sends every request to it. DA per 1M tokens: ↑ what you send.
| Provider | ↑ text | Latency | Uptime |
|---|---|---|---|
| Cohere | 39,94 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.
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.embeddings.create(
model="cohere/embed-5-pro",
input="Delivery to Oran takes two days.",
)
print(resp.data[0].embedding[:5])Runs this request once on your balance.
About 0,040 DA per page. ↑ 39,94 DA per 1M tokens.
No. You pay per use from your balance, with no subscription. Run it once from Call it in code, at the same price.
This model accepts text and pictures as input and outputs numerical representations of the content. It can process up to 120 pages of material at once and generate up to 110 pages of output. It is designed to be a higher accuracy tier within its family of models. This model is limited to processing and outputting these representations and cannot perform tasks requiring complex reasoning.
Embed 5 Fast costs 0,013 DA less for the same page.
Deposit dinars with your Edahabia or CIB card. Every model, Embed 5 Pro included, is paid from that balance. No foreign card, no conversion.
Cohere names no languages for Embed 5 Pro. Arabic, French and Darja: not stated.
Up to 128 000 tokens. Split anything longer.
Not stated.
Cohere. Released 29 October 2026.
Rerank 4 Fast takes a search question and a list of candidate documents and returns them ordered by relevance, reading up to about 32 pages per document, question included, in more than 100 languages. It is the lighter of the two Rerank 4 models, suited to quick replies and heavy traffic, so use it where many searches arrive at once.
You send Rerank 4 Pro a search question and a list of candidate documents, and it returns them ordered by relevance. Each document, question included, can run to about 32 pages, in more than 100 languages, and data records are accepted alongside text. Use it as a second pass after a keyword search or a search by meaning, for hard questions and long documents where result quality counts most. Rerank 4 Fast is the lighter version for quick replies; Rerank v3.5 reads only about 4 pages per document.
Cohere's earlier reranker, from before Rerank 4, reordering semantic or keyword search results by relevance and handling multi-aspect and semi-structured data across more than 100 languages
This model accepts text and pictures as input to generate numerical representations of the content. It can process up to 120 pages of material simultaneously. Its design focuses on being a fast and economical option for content representation tasks. The model is limited to processing and outputting these representations and cannot perform tasks requiring complex reasoning or generating new written material.
From what its maker and two benchmark sites publish, and where it stands on OpenDunes. Read 7 Nov 2026.
Process text and images to generate numerical representations