May 18, 2026 - 2 min read

Mistral Model Analysis: An Overview into AI Capabilities

In this post, we'll explore the capabilities of Mistral AI models through a custom classification system. We've developed a Python script that analyzes model data, classifies models based on their capabilities, and presents the findings in a HTML format.

Background

Mistral AI offers a variety of models with different capabilities. To better understand and compare these models, we've created a custom classification system that groups models based on their primary capabilities. This analysis is based on the model data as of May 17, 2026.

The Classification System

We've developed a modified version of async_list_models.py that:

  1. Loads model data from JSON
  2. Classifies models into logical groups based on their capabilities
  3. Calculates capability scores for ranking within groups
  4. Generates a HTML report

The classification system groups models into these categories:

  • Transcription: Models specialized in converting audio to text
  • Speech: Models specialized in text-to-speech conversion
  • Audio Understanding: Models that understand audio content beyond transcription
  • Vision: Models with image and video processing capabilities
  • Chat: General purpose chat and conversation models
  • Reasoning: Models with advanced reasoning and problem-solving capabilities
  • Code Completion: Models specialized in code generation and completion
  • Fine Tuning: Models that can be fine-tuned for specific tasks
  • Classification: Models specialized in categorizing and moderating content
  • Other: Models with capabilities that don't fit into the other groups

Capability Scores

It's important to note that the capability scores used in this analysis are not measures of the models' intrinsic capabilities. They are solely used to rank models within their capability groups for better organization in this analysis. The scoring system assigns weights to different capabilities based on their relative importance and complexity.

The Analysis Report

We've generated a HTML report that presents the model data in a structured and organized way. You can download the full report model_analysis.html

Key Findings

  1. Diverse Capabilities: Mistral AI offers models with a wide range of capabilities, from basic chat to advanced reasoning and specialized tasks like transcription and code completion.

  2. Specialized Models: There are several specialized models for niche tasks like audio transcription, text-to-speech conversion, and optical character recognition.

  3. Reasoning Models: The reasoning models stand out with their advanced capabilities, making them suitable for complex problem-solving tasks.

  4. Fine-Tuning Options: Multiple models are available for fine-tuning, allowing users to adapt the models to their specific needs.

Conclusion

This analysis provides a comprehensive overview of Mistral AI's model capabilities. By classifying models based on their primary capabilities and using capability scores for ranking, we've created a structured and organized view of the available models.

The HTML report allows you to explore the data in detail, view model capabilities, and compare models within their capability groups. We hope this analysis helps you better understand Mistral AI's offerings and choose the right model for your specific needs.

Download the Data

You can download the original JSON data used for this analysis mistral-modelcards-data.json.

About the Code

The analysis was performed using Python with the following key libraries:

  • pandas for data manipulation
  • matplotlib for visualization
  • json for data loading