by ElorianReleased 17 October 2026
Glimpse takes text, images and video and answers in text, reasoning about what it sees rather than just describing it. It keeps about 260 pages in mind at once and can use the tools you connect. Give it jobs where the answer sits in the picture: images and video of the physical world that must be read closely and reasoned over.
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 | 199,70 DA | 998,51 DA |
| Cached tokens read | 19,97 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 | Cache read | Latency | Throughput | Uptime |
|---|---|---|---|---|---|---|
| Together | 199,70 DA | 998,51 DA | 19,97 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.
What's the total on this invoice, and when is it due?
invoice-scan.jpg · photoThe total is 42 300,00 DA, due 5 September 2026. Worth a double-check: the handwritten day could read as 8 instead of 3.
Try in Chat LabTurn this customer email into JSON with intent, urgency and order_id.
customer-email.txtTry 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="elorian/glimpse",
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_pstopfrequency_penaltypresence_penaltyrepetition_penaltylogit_biaslogprobstop_logprobsReasoning
Let it think before answering — and see the thinking.
reasoninginclude_reasoningStructured output
Get JSON you can parse instead of prose.
response_formatstructured_outputsTools
Let the model call your functions.
toolstool_choiceAbout 0,70 DA per message. ↑ 199,70 DA · ↓ 998,51 DA per 1M tokens.
No. You pay per use from your balance, with no subscription. Try it in Chat at the same price.
Glimpse takes text, images and video and answers in text, reasoning about what it sees rather than just describing it. It keeps about 260 pages in mind at once and can use the tools you connect. Give it jobs where the answer sits in the picture: images and video of the physical world that must be read closely and reasoned over.
Deposit dinars with your Edahabia or CIB card. Every model, Glimpse included, is paid from that balance. No foreign card, no conversion.
Elorian names no languages for Glimpse. Arabic, French and Darja: not stated.
It reads text, images and video. Up to 262K tokens in one request, about 260 pages. It writes up to 192 000 words at once.
No. Elorian has not published its weights.
Elorian. Released 17 October 2026.
From what its maker and two benchmark sites publish, and where it stands on OpenDunes. Read 7 Nov 2026.
Thinks first
Works through the problem before it answers.
Uses your tools
Can call functions your code provides.
Fills your JSON
Answers in the JSON shape you give it.
Searches the web No.
Can look things up online while it answers.
Cheaper on repeats
A prompt it saw a moment ago costs less the second time.
Reads video frames and images up to 262144 tokens at once and returns reasoned text answers
Thinks first
Fills your JSON schema from what it sees in images and video
Fills your JSON