Mistral Large 3

VisionTool use

Mistral's flagship 675B parameter model with state-of-the-art reasoning, coding, and multilingual capabilities with vision support.

Model id — paste this in your code

mistralai/mistral-large-3

Pricing · per 1M tokens

Show prices in

Input150 DA$0.6

Output450 DA$1.80

Cached input150 DA$0.6

Context window256KMax output: 33K

Capabilities

Vision — Understands images and documents you send
Tool use — Can call your functions / tools

Estimate your cost

Input tokens Output tokens Requests

Estimated cost

Use this model

Create an account, top up in dinars and call it with your key:

from openai import OpenAI

client = OpenAI(
    base_url="https://dzrouter.com/v1",
    api_key="sk-dz-…",
)

reply = client.chat.completions.create(
    model="mistralai/mistral-large-3",
    messages=[{"role": "user", "content": "Salam!"}],
)
print(reply.choices[0].message.content)

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://dzrouter.com/v1",
  apiKey: process.env.DZROUTER_API_KEY,
});

const reply = await client.chat.completions.create({
  model: "mistralai/mistral-large-3",
  messages: [{ role: "user", content: "Salam!" }],
});
console.log(reply.choices[0].message.content);

curl https://dzrouter.com/v1/chat/completions \
  -H "Authorization: Bearer $DZROUTER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "mistralai/mistral-large-3",
    "messages": [{"role": "user", "content": "Salam!"}],
    "stream": true
  }'

from anthropic import Anthropic

client = Anthropic(
    base_url="https://dzrouter.com",
    api_key="sk-dz-…",
)

msg = client.messages.create(
    model="mistralai/mistral-large-3",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Salam!"}],
)
print(msg.content[0].text)

Create a free account

More from Mistral

mistralai/mistral-nemoMistral

mistralai/mistral-nemo

Input5.7 DA

Output9 DA

Context131K

mistralai/mistral-small-2603Mistral

mistralai/mistral-small-2603

Input45 DA

Output180 DA

Context350K

Mistral SmallMistral

mistralai/mistral-small-3.2-24b-instruct

Mistral's efficient 24B model optimized for simple tasks with low latency and 128K context. Great for classification, customer support, text generation, and multimodal tasks.

Input22.5 DA

Output60 DA

Context128K

mistralai/mistral-medium-3-5Mistral

mistralai/mistral-medium-3-5

Input450 DA

Output2,250 DA

Context128K

mistralai/mistral-large-2512Mistral

mistralai/mistral-large-2512

Input150 DA

Output450 DA