by PerplexityReleased 16 October 2026
Decider V1.2 does not write text. You send content as text, a table of data or a picture, plus named questions of three kinds: yes or no, a choice among as many as 255 options, or a score on an ordered scale. It returns the probability of every answer, so your own system sets its thresholds for sorting, routing or moderation. It is the larger model of the pair and reads about 262 pages; Decider Flash V1.2 is the smaller, lower-cost version.
You pay for what each request uses. No subscription, no minimum.
One case, the ordinary use
Every rate
| Meter | ↑ you send | ↓ comes back |
|---|---|---|
| Text tokens | 6,66 DA |
per 1M tokens
Two companies run this model. OpenDunes sends each request to one of them, picked by price and speed. If it fails, the next one takes it. DA per 1M tokens: ↑ what you send.
| Provider | ↑ Sent | Latency | Uptime |
|---|---|---|---|
| Makora | 6,32 DA | … | … |
| Perplexity | 6,66 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.
One HTTP call, with your questions named as you like.
import os, requests
BASE = "https://opendunes.com"
KEY = os.environ["OPENDUNES_API_KEY"]
H = {"Authorization": f"Bearer {KEY}"}
resp = requests.post(f"{BASE}/alpha/decisions", headers=H, json={
"model": "perplexity/pplx-decider-v1.2",
"state": "The courier came two days late and the box was open.",
"questions": {
"is_complaint": {
"type": "noul",
"instructions": "Is it a complaint?",
"criteria": {
"true": "The customer is unhappy with the service.",
"false": "The customer is asking a question or saying thanks.",
},
},
},
})
print(resp.json())Runs this request once on your balance.
About 0,0067 DA per case. ↑ 6,66 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.
Decider V1.2 does not write text. You send content as text, a table of data or a picture, plus named questions of three kinds: yes or no, a choice among as many as 255 options, or a score on an ordered scale. It returns the probability of every answer, so your own system sets its thresholds for sorting, routing or moderation. It is the larger model of the pair and reads about 262 pages; Decider Flash V1.2 is the smaller, lower-cost version.
Decider Flash V1.2 costs 0,0034 DA less for the same case.
Deposit dinars with your Edahabia or CIB card. Every model, Decider V1.2 included, is paid from that balance. No foreign card, no conversion.
Perplexity names no languages for Decider V1.2. Arabic, French and Darja: not stated.
Yes or no, one choice from your list, or a score on your scale. Each answer comes with its probability.
Perplexity. Released 16 October 2026.
Embed V1 0.6B turns text of up to about 32 pages into a fingerprint of its meaning, a list of 1,024 numbers, so search finds text that means the same thing. It needs no special instruction before the text and is built for large-scale search over independent texts, search queries and single sentences. It is the small, quick model of the pair.
Embed V1 4B turns text of up to about 32 pages into a fingerprint of its meaning, a list of 2,560 numbers, so search finds text that means the same thing. It needs no special instruction before the text and is built for large-scale search over independent texts, search queries and single sentences. It is the larger model of the pair, tuned for the best result quality.
Decider Flash V1.2 does not write text. You send content as text, a table of data or a picture, plus named questions: yes or no, a choice among as many as 255 options, or a score on an ordered scale. It returns a probability for every answer, so your own system sets its thresholds for sorting, routing or moderating high volumes.
Sonar answers a question with a web search behind it: you send text or a picture and get a written answer with citations, and you can choose which sources it draws on. It keeps about 127 pages in mind at once and is the lightest, fastest model of the Sonar line, meant for question-and-answer features inside an app.
From what its maker and two benchmark sites publish, and where it stands on OpenDunes. Read 7 Nov 2026.
Read text and image state up to 262,144 tokens and return a decision without generating prose
Replace a Decider V1.1 27B deployment with no API contract changes