opendunes

Kimi K3.1 Pro

New

by Moonshot AIReleased 23 October 2026

#1 for interface designThis model accepts text, pictures, and video, allowing it to read up to 1000 pages of information at once. It is designed to handle complex, long-running coding and reasoning tasks. A key feature is its ability to process visual and auditory data alongside written text. However, it is limited to generating text responses and cannot search the internet.

TakesTextImagesVideo
GivesText

What it costs

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

≈ 2,33 DA per message3 000 DA buys about 1 200 messages

One message, the ordinary use

1 000 tokens sent× 665,67 DA per 1M0,67 DA
500 tokens back× 3 328,36 DA per 1M1,66 DA
Total≈ 2,33 DA

Every rate

Meter↑ you send↓ comes back
Text tokens665,67 DA3 328,36 DA
Cached tokens read66,57 DA

per 1M tokens

Analyzing a large document for key insights≈ 665,67 DA
Responding to a detailed query involving multiple inputs≈ 1 997,02 DA
Generating a comprehensive technical report≈ 3 128,66 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

17 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.

Relace…
↑ Sent, per 1M
109,40 DA
↓ Back, per 1M
2 700,96 DA
Cache read
66,57 DA
Latency
…
Throughput
…
Sail ResearchUnited States…
↑ Sent, per 1M
115,16 DA
↓ Back, per 1M
5 518,75 DA
Cache read
57,58 DA
Latency
…
Throughput
…
Sail Research…
↑ Sent, per 1M
115,16 DA
↓ Back, per 1M
5 518,75 DA
Cache read
57,58 DA
Latency
…
Throughput
…
AkashML…
↑ Sent, per 1M
582,46 DA
↓ Back, per 1M
3 328,36 DA
Cache read
59,91 DA
Latency
…
Throughput
…
PrimaLabs…
↑ Sent, per 1M
599,10 DA
↓ Back, per 1M
2 995,52 DA
Cache read
59,91 DA
Latency
…
Throughput
…
Wafer…
↑ Sent, per 1M
599,10 DA
↓ Back, per 1M
2 995,52 DA
Cache read
59,91 DA
Latency
…
Throughput
…
InferenceNet…
↑ Sent, per 1M
599,10 DA
↓ Back, per 1M
2 995,52 DA
Cache read
59,91 DA
Latency
…
Throughput
…
InferenceNetUnited States…
↑ Sent, per 1M
599,10 DA
↓ Back, per 1M
2 995,52 DA
Cache read
59,91 DA
Latency
…
Throughput
…
DeepInfra5 % offUnited States…
↑ Sent, per 1M
Was 665,67632,39 DA
↓ Back, per 1M
Was 3 328,363 161,94 DA
Cache read
Was 66,5763,24 DA
Latency
…
Throughput
…
MorphUnited States…
↑ Sent, per 1M
635,05 DA
↓ Back, per 1M
3 994,03 DA
Cache read
156,43 DA
Latency
…
Throughput
…
Fireworks…
↑ Sent, per 1M
665,67 DA
↓ Back, per 1M
3 328,36 DA
Cache read
66,57 DA
Latency
…
Throughput
…
WaferUnited States…
↑ Sent, per 1M
665,67 DA
↓ Back, per 1M
3 328,36 DA
Cache read
66,57 DA
Latency
…
Throughput
…
PhalaUnited States…
↑ Sent, per 1M
665,67 DA
↓ Back, per 1M
3 328,36 DA
Cache read
66,57 DA
Latency
…
Throughput
…
DigitalOcean…
↑ Sent, per 1M
665,67 DA
↓ Back, per 1M
3 328,36 DA
Cache read
66,57 DA
Latency
…
Throughput
…
Parasail…
↑ Sent, per 1M
665,67 DA
↓ Back, per 1M
3 328,36 DA
Cache read
66,57 DA
Latency
…
Throughput
…
Modal…
↑ Sent, per 1M
665,67 DA
↓ Back, per 1M
3 328,36 DA
Cache read
66,57 DA
Latency
…
Throughput
…
Phala…
↑ Sent, per 1M
665,67 DA
↓ Back, per 1M
3 328,36 DA
Cache read
66,57 DA
Latency
…
Throughput
…
Nebius…
↑ Sent, per 1M
665,67 DA
↓ Back, per 1M
3 328,36 DA
Cache read
66,57 DA
Latency
…
Throughput
…
Together…
↑ Sent, per 1M
665,67 DA
↓ Back, per 1M
3 328,36 DA
Cache read
66,57 DA
Latency
…
Throughput
…
Moonshot AIAsia…
↑ Sent, per 1M
665,67 DA
↓ Back, per 1M
3 328,36 DA
Cache read
66,57 DA
Latency
…
Throughput
…
AlibabaAsia…
↑ Sent, per 1M
765,52 DA
↓ Back, per 1M
3 827,61 DA
Cache read
76,55 DA
Latency
…
Throughput
…
Provider↑ Sent↓ BackCache readLatencyThroughputUptime
Relace109,40 DA2 700,96 DA66,57 DA………
Sail ResearchUnited States115,16 DA5 518,75 DA57,58 DA………
Sail Research115,16 DA5 518,75 DA57,58 DA………
AkashML582,46 DA3 328,36 DA59,91 DA………
PrimaLabs599,10 DA2 995,52 DA59,91 DA………
Wafer599,10 DA2 995,52 DA59,91 DA………
InferenceNet599,10 DA2 995,52 DA59,91 DA………
InferenceNetUnited States599,10 DA2 995,52 DA59,91 DA………
DeepInfra5 % offUnited StatesWas 665,67632,39 DAWas 3 328,363 161,94 DAWas 66,5763,24 DA………
MorphUnited States635,05 DA3 994,03 DA156,43 DA………
Fireworks665,67 DA3 328,36 DA66,57 DA………
WaferUnited States665,67 DA3 328,36 DA66,57 DA………
PhalaUnited States665,67 DA3 328,36 DA66,57 DA………
DigitalOcean665,67 DA3 328,36 DA66,57 DA………
Parasail665,67 DA3 328,36 DA66,57 DA………
Modal665,67 DA3 328,36 DA66,57 DA………
Phala665,67 DA3 328,36 DA66,57 DA………
Nebius665,67 DA3 328,36 DA66,57 DA………
Together665,67 DA3 328,36 DA66,57 DA………
Moonshot AIAsia665,67 DA3 328,36 DA66,57 DA………
AlibabaAsia765,52 DA3 827,61 DA76,55 DA………

You pay the price of the provider that served your request. Prices read 15:06 · 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.

Understands images
You send

What's the total on this invoice, and when is it due?

invoice-scan.jpg · photo
It replied

The 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 Lab
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

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
moonshotai/kimi-k3.1-pro
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="moonshotai/kimi-k3.1-pro",
    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.

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.

reasoningreasoning_effortinclude_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 Kimi K3.1 Pro

  • How much does Kimi K3.1 Pro cost in dinars?

    About 2,33 DA per message. ↑ 665,67 DA · ↓ 3 328,36 DA per 1M tokens.

  • Is Kimi K3.1 Pro 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 Kimi K3.1 Pro best for?

    #1 for interface design · This model accepts text, pictures, and video, allowing it to read up to 1000 pages of information at once. It is designed to handle complex, long-running coding and reasoning tasks. A key feature is its ability to process visual and auditory data alongside written text. However, it is limited to generating text responses and cannot search the internet.

  • How do I pay for Kimi K3.1 Pro without an international card?

    Deposit dinars with your Edahabia or CIB card. Every model, Kimi K3.1 Pro included, is paid from that balance. No foreign card, no conversion.

  • Does Kimi K3.1 Pro work in Arabic, French or Darja?

    Moonshot AI names no languages for Kimi K3.1 Pro. Arabic, French and Darja: not stated.

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

    It reads text, images and video. Up to 1M tokens in one request, about 1 000 pages. It writes up to 708 000 words at once.

  • Is Kimi K3.1 Pro open source?

    Yes, its weights are public. Open weights on Hugging Face

  • Who makes Kimi K3.1 Pro, and when was it released?

    Moonshot AI. Released 23 October 2026.

Other Moonshot AI models, priced in dinars

See all Moonshot AI models
Kimi K3Moonshot AI · Jul 16, 2026

#3 for websites · Kimi K3 reads text, pictures and video and writes text back, taking in about a thousand pages at once. You can download it and run it yourself, and it thinks before it answers. It is built for work inside large code projects: it uses connected tools, finds bugs, and revises its code from screenshots, log files, test results and what happens when the program runs.

#18 of 119 for codingThinks firstUses your tools
≈2,73 DAper message
View model
Kimi K2.6Moonshot AI · Apr 20, 2026

#2 for slide decks · Kimi K2.6 reads text and pictures and writes text back, keeping about 256 pages in mind, and it thinks before it answers unless you switch that off for quicker replies. It is aimed at long coding runs across Go, Rust and Python projects and at turning a written description or a mock-up into a working screen, and it can split a job across hundreds of helper copies of itself working side by side.

Thinks firstUses your tools260 pages at once
≈0,78 DAper message
View model
Kimi K2.7 CodeMoonshot AI · Jun 12, 2026

The coding-focused Kimi K2, which always thinks and keeps its full reasoning from turn to turn, reading text and images over 256K for end-to-end programming and breaking agent tasks into steps

Thinks firstUses your tools260 pages at once
≈0,78 DAper message
View model
Kimi K2.5Moonshot AI · Jan 27, 2026

Kimi K2.5 reads text and pictures and writes text back, and it keeps about 256 pages in mind at once. It is built to turn a picture, such as a mock-up of a screen, into working code, and to use the tools you connect to it on its own; Moonshot trained it on pictures and text together, on top of Kimi K2. Kimi K2.6 is the later release for longer coding runs and screen building.

Thinks firstUses your tools260 pages at once
≈0,58 DAper message
View model