opendunes

Ling 3.1 Flash

by InclusionaiReleased 2 October 2026

Ling 3.1 Flash is a text model from inclusionAI that mixes quick answers with thinking first. It reads up to about 262 pages at once, can write up to about 236 pages in a single reply, and can use tools or fill in an exact form you give it. Pick it when one request needs a very long answer.

TakesText
GivesText
Open in chatCreate API keyCompare

What it costs

You pay for what each request uses. No subscription, no minimum.

≈ 0,037 DA per message3 000 DA buys about 80 000 messages

85 % offNovita has cut its price. Every figure here is the new one.

One message, the ordinary use

1 000 tokens sent× 14,98 DA per 1M0,015 DA
500 tokens back× 44,93 DA per 1M0,022 DA
Total≈ 0,037 DA

Every rate

Meter↑ you send↓ comes back
Text tokens14,98 DA44,93 DA
Cached tokens read3,00 DA

per 1M tokens

Drafting a step-by-step solution to a multi-part maths problem≈ 0,15 DA
Planning and executing a tool-assisted research workflow≈ 0,43 DA
Summarising a long technical report with key findings pulled out≈ 0,99 DA
Answering questions across a full codebase loaded in one prompt≈ 2,31 DA
When you pay
After the answer, from your balance. Nothing is held.
Why it varies
A longer question or a longer answer costs more.
After each one
The exact charge shows on the request.
DepositDeposits from 50 DA, with Edahabia or CIB.

Where your request runs

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 · ↓ what comes back.

Novita85 % off…
↑ Sent, per 1M
Was 99,8714,98 DA
↓ Back, per 1M
Was 299,5344,93 DA
Cache read
Was 20,003,00 DA
Latency
…
Throughput
…
DeepInfra75 % offUnited States…
↑ Sent, per 1M
Was 99,8424,96 DA
↓ Back, per 1M
Was 299,5674,89 DA
Cache read
Was 19,964,99 DA
Latency
…
Throughput
…
Provider↑ Sent↓ BackCache readLatencyThroughputUptime
Novita85 % offWas 99,8714,98 DAWas 299,5344,93 DAWas 20,003,00 DA………
DeepInfra75 % offUnited StatesWas 99,8424,96 DAWas 299,5674,89 DAWas 19,964,99 DA………

You pay the price of the provider that served your request. Prices read 15:19 · speed over the last 30 minutes · uptime over 3 days.

See it in action

Real requests, real replies. Try any of them yourself — one click, pre-filled.

Structured output
You send

Turn this customer email into JSON with intent, urgency and order_id.

customer-email.txt
It replied

{ "intent": "refund", "urgency": "high", "order_id": "OD-58421" }

Try in Chat Lab
Writing
You send

Two lines to welcome a shop in Oran.

It replied

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 Lab

Try your own request — same model, pre-selected.

Open Chat Lab

Call it in code

Swap the base URL and the key. Your OpenAI code runs unchanged.

POST /v1/chat/completions
Base URL
https://opendunes.com/v1
Model ID
inclusionai/ling-3.1-flash
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="inclusionai/ling-3.1-flash",
    messages=[{"role": "user", "content": "Two lines to welcome a shop in Oran."}],
)

print(resp.choices[0].message.content)
pip install openaiFull reference for this route
Sign in to run it

Runs this request once on your balance.

Parameters you can send

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_biaslogprobstop_logprobs

Reasoning

Let it think before answering — and see the thinking.

reasoninginclude_reasoning

Structured output

Get JSON you can parse instead of prose.

response_formatstructured_outputs

Tools

Let the model call your functions.

toolstool_choice

Questions about Ling 3.1 Flash

  • How much does Ling 3.1 Flash cost in dinars?

    About 0,037 DA per message. Was 0,25 DA. ↑ 14,98 DA · ↓ 44,93 DA per 1M tokens.

  • Is Ling 3.1 Flash free? Can I try it?

    No. You pay per use from your balance, with no subscription. Try it in Chat at the same price.

  • What is Ling 3.1 Flash best for?

    Ling 3.1 Flash is a text model from inclusionAI that mixes quick answers with thinking first. It reads up to about 262 pages at once, can write up to about 236 pages in a single reply, and can use tools or fill in an exact form you give it. Pick it when one request needs a very long answer.

  • How do I pay for Ling 3.1 Flash without an international card?

    Deposit dinars with your Edahabia or CIB card. Every model, Ling 3.1 Flash included, is paid from that balance. No foreign card, no conversion.

  • Does Ling 3.1 Flash work in Arabic, French or Darja?

    Inclusionai names no languages for Ling 3.1 Flash. Arabic, French and Darja: not stated.

  • Can it read PDFs, images or a whole book?

    It reads text. Up to 1M tokens in one request, about 1 000 pages. It writes up to 197 000 words at once.

  • Is Ling 3.1 Flash open source?

    No. Inclusionai has not published its weights.

  • Who makes Ling 3.1 Flash, and when was it released?

    Inclusionai. Released 2 October 2026.

Other Inclusionai models, priced in dinars

See all Inclusionai models
Ling 3.0 FlashInclusionai · Jul 23, 2026

Ling 3.0 Flash is a text model from inclusionAI, built to finish automated tasks using less text, which keeps cost and waiting down. You send up to about 262 pages of text, with tools if you wish, and get text back. Use it for high-volume automated tasks where the amount of text used and speed set your limits.

Thinks firstUses your tools260 pages at once
≈0,017 DAper message
View model
Ling 3.0 Flash VLInclusionai · Sep 10, 2026

Ling 3.0 Flash VL reads text, pictures and video and answers in text, so you can send a screenshot, a photo or a clip along with your question. It can switch between an instant answer and thinking first, and it can use tools, which suits automated helpers that must act on what is on a screen. It reads about 131 pages at once.

Thinks firstUses your tools130 pages at once
≈0,050 DAper message
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Ling 3.0 TinyInclusionai · Nov 5, 2026

This model processes text input up to 260 pages and produces text output up to 250 pages. It is best suited for complex instruction following and managing multi-turn conversations for automated workflows. A key feature is its ability to act as a responsive agent and utilize provided tools. However, it does not have the capability to search the web or access external information.

Thinks firstUses your tools260 pages at once
≈0,012 DAper message
View model