Mistral: Pixtral Large 2411

Pixtral Large is a 124-billion-parameter multimodal model from Mistral AI. It excels in understanding both images and text. Built on the Mistral Large 2 framework, it offers advanced capabilities for image and document analysis. This model achieves top scores in benchmarks like Math Vista and DocVQA. Its design allows for effective reasoning across visual and textual data.

import OpenAI from "openai"

const openai = new OpenAI({
  baseURL: "https://api.aiapilab.com/v1",
  apiKey: $AIAPILAB_API_KEY
})

async function main() {
  const completion = await openai.chat.completions.create({
    model: "mistralai/pixtral-large-2411",
    messages: [
      {
        "role": "user",
        "content": [
          {
            "type": "text",
            "text": "What's in this image?"
          },
          {
            "type": "image_url",
            "image_url": {
              "url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
            }
          }
        ]
      }
    ]
  })

  console.log(completion.choices[0].message)
}
main()

from openai import OpenAI

client = OpenAI(
  base_url="https://api.aiapilab.com/v1",
  api_key="$AIAPILAB_API_KEY",
)

completion = client.chat.completions.create(
  model="mistralai/pixtral-large-2411",
  messages=[
    {
      "role": "user",
      "content": [
        {
          "type": "text",
          "text": "What's in this image?"
        },
        {
          "type": "image_url",
          "image_url": {
            "url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
          }
        }
      ]
    }
  ]
)
print(completion.choices[0].message.content)

Mistral: Pixtral Large 2411

Context128000

Input$2 / M

Output$6 / M

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Description

Mistral AI has launched Pixtral Large 2411. This groundbreaking multimodal model was released in December 2024. It features a powerful 124 billion parameters. The model combines image processing and text generation seamlessly. Pixtral Large excels in benchmarks, scoring an impressive 69.4% on Math Vista. This score highlights its strong math skills using visual data.

Additionally, Pixtral Large outperforms competitors like GPT-4 and Gemini-1.5. It excels in document and chart comprehension tasks. The model supports complex document analysis. With a context window of 128,000 tokens, it can handle large data sets quickly. Users can input text and up to 30 high-resolution images at once.

The architecture includes a 1 billion parameter vision encoder. This enhances its ability to understand visual information. Furthermore, it supports structured visual reasoning tasks. This is useful for industries needing strong image-text integration. While it is not designed for optical character recognition, Mistral AI plans to improve these features in future updates.

Pixtral Large is available for academic and enterprise use. Users can access it through the Pixtral Large API. This ensures easy integration into existing workflows. Its design empowers researchers and developers to create innovative applications. As a result, Pixtral Large stands out in the AI landscape.

Using Mistral AI's services to integrate this model provides better opportunities and results. Get a better price by using our AIAPILAB services for integration.

Model API Use Case

Pixtral Large 2411 is a strong multimodal API. It is made for advanced image and text processing. This model has 124 billion parameters. It does well in tasks that need both visual and textual reasoning. 

For example, it scored a great 69.4% on the Math Vista benchmark. This is better than all the models before it. 

In finance, automated document analysis is very important. Pixtral Large can read complex financial statements. It extracts key figures and summarizes insights. This helps analysts work faster and focus on important decisions.

An e-commerce platform can also use Pixtral Large. It can help with image recognition and creating product descriptions. By looking at user-uploaded images, the API makes accurate descriptions. It also suggests similar items, which boosts customer engagement and sales.

Additionally, the API can handle up to 30 high-resolution images with text. This is perfect for education and research, where visuals help with understanding.

With its strong performance and flexibility, Pixtral Large 2411 offers new chances for innovation. For more information, check the official documentation.

Model Review

Pros

1. Pixtral Large processes text and images in tandem, enhancing user experience. 2. It decodes complex documents and charts, revealing insights effortlessly. 3. The model grasps visual data, enabling precise interpretations and analyses. 4. A vast context window allows quick processing of extensive datasets. 5. Its architecture fosters innovation, empowering developers to build unique applications.

Cons

1. Pixtral Large demands substantial computational resources. Users need powerful GPUs for optimal performance. 2. The model may exhibit biases in its outputs. This can affect the accuracy of generated content. 3. Current limitations exist in optical character recognition. Users may find this feature lacking for specific tasks.

Comparison

Feature/Aspect	GPT-4	Mistral Large 2407	Mistral: Pixtral Large 2411
Model Type	Text-only	Text-only	Multimodal (text and image)
Parameters	175 billion	24 billion	124 billion (with 1 billion vision encoder)
Context Window	8,192 tokens	32,000 tokens	128,000 tokens
Integration Capabilities	Excellent in language understanding and generation	Strong reasoning and text generation	Advanced document interpretation and image understanding
Performance on Benchmarks	Leading performance in various benchmarks	High performance in text tasks	Superior in multimodal tasks (e.g., 69.4% on Math Vista)

API

import OpenAI from "openai"

const openai = new OpenAI({
  baseURL: "https://api.aiapilab.com/v1",
  apiKey: $AIAPILAB_API_KEY
})

async function main() {
  const completion = await openai.chat.completions.create({
    model: "mistralai/pixtral-large-2411",
    messages: [
      {
        "role": "user",
        "content": [
          {
            "type": "text",
            "text": "What's in this image?"
          },
          {
            "type": "image_url",
            "image_url": {
              "url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
            }
          }
        ]
      }
    ]
  })

  console.log(completion.choices[0].message)
}
main()

from openai import OpenAI

client = OpenAI(
  base_url="https://api.aiapilab.com/v1",
  api_key="$AIAPILAB_API_KEY",
)

completion = client.chat.completions.create(
  model="mistralai/pixtral-large-2411",
  messages=[
    {
      "role": "user",
      "content": [
        {
          "type": "text",
          "text": "What's in this image?"
        },
        {
          "type": "image_url",
          "image_url": {
            "url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
          }
        }
      ]
    }
  ]
)
print(completion.choices[0].message.content)

FAQ

Q1: What is Pixtral Large 2411?  
A1: Pixtral Large 2411 is a multimodal model combining text and image processing.

Q2: How can I access Pixtral Large 2411?  
A2: Use the Pixtral Large API to send requests and receive responses.

Q3: What tasks can Pixtral Large perform?  
A3: Pixtral Large excels at image understanding, text generation, and reasoning tasks.

Q4: What are the input requirements for Pixtral Large?  
A4: Provide text and images in your API request for optimal processing.

Q5: How does Pixtral Large handle multilingual tasks?  
A5: Pixtral Large supports various languages, enhancing its global usability.