Mistral Large: Mistral AI’s Multilingual AI Transforming Coding and Math

Overview

Mistral Large is the latest flagship Large Language Model (LLM) developed by Mistral AI, a Paris-based AI startup that is gradually building an alternative to OpenAI and Anthropic. The model was first made available on Azure and the Mistral AI platform in February 2024, attracting thousands of developers and researchers to try it out. The development of Mistral Large marks a significant milestone in the expansion of Mistral AI, propelling its innovative research and practical applications to new customers everywhere.

Key Features of Mistral Large

Mistral Large is a marvel in the realm of AI, a state-of-the-art reasoning and knowledge model that stands out in the crowd. It employs a unique architecture and an innovative training methodology, pushing the boundaries of what AI can achieve. With the capacity to handle up to 32K tokens, it is a powerhouse in generating, reviewing, and commenting on code, providing support for all mainstream programming languages. This makes it an invaluable tool for developers across the globe.

source - https://mistral.ai/news/mistral-large/

But that’s not all. Mistral Large is designed with a multilingual approach, offering unparalleled performance (as shown in figure above) in English, French, German, Spanish, and Italian. It doesn’t stop there, though. It also extends its linguistic prowess to dozens of other languages, delivering high accuracy and fluency. This makes Mistral Large a truly global AI model, breaking down language barriers and fostering global collaboration.

Benefits of Using Mistral Large

The benefits of using Mistral Large are manifold. For developers and researchers, it can be a game-changer, enhancing productivity and sparking creativity. By offering relevant suggestions, feedback, and solutions, it can help speed up workflows and generate new ideas. It also bolsters accuracy and reliability by scrutinizing inputs and outputs to ensure they meet the desired specifications and standards. This can help users avoid errors and inconsistencies, ensuring high-quality results. Furthermore, Mistral Large can help users craft engaging and personalized content for their audiences. By adapting their tone, style, and language to suit their preferences and needs, it can help create content that truly resonates with the audience. This can lead to increased customer satisfaction and engagement, making Mistral Large a valuable asset for any organization.

Performance Evaluation with other models

Mistral Large, the crown jewel of Mistral AI, has made waves in the AI industry with its advanced capabilities. It has been put to the test on numerous benchmarks, demonstrating robust performance, especially in coding and mathematical tasks. For example, it outperformed its competitors on standardized evaluation sets for coding tasks like HumanEval (second only to GPT-4) and MBPP. It also topped the charts on Mathematics benchmarks like GSM8K.

source - https://mistral.ai/news/mistral-large/

When compared to other models, Mistral Large has been hailed as a formidable contender, rubbing shoulders with giants like OpenAI’s GPT-4, Anthropic’s Claude 2, and Google’s Gemini Pro. It has also been juxtaposed with ChatGPT, Gemini, and Claude. Despite the intense competition, Mistral Large has managed to carve a unique space for itself with its distinctive features and capabilities.

source - https://mistral.ai/news/mistral-large/

Please refer to the link provided at the end of the article to learn more about various benchmarks and it's corresponding results.

Model Variations 

Mistral AI’s OSS models, Mixtral-8x7B and Mistral-7B, were added to the Azure AI model catalog in December 2023. These models are open-source and free to use for anyone who wants to explore the capabilities of Mistral AI. Mixtral-8x7B is a hybrid model that combines eight different experts, each specialized in a different domain, such as code, math, science, or literature. Mistral-7B is a general-purpose model that can handle a wide range of tasks and domains. The addition of Mistral Large to the Mistral AI collection of models in the Azure AI model catalog marks the expansion of the company’s offerings. Mistral Large is a premium model that requires a subscription to access and use. It is the most advanced and powerful model in the Mistral AI portfolio, offering superior performance and functionality.

Architectural Brilliance of Mistral Models

Mistral models, such as the flagship Mistral Large and its sibling Mistral 7B, demonstrate the power of innovative architecture and training methodology to achieve remarkable performance in natural language processing. They use a decoder-only Transformer, a design choice that empowers them to master various tasks and domains. This architecture cleverly balances high performance with memory optimization, using attention mechanisms and caching strategies that make them faster and better than larger models.

One of the key architectural breakthroughs in Mistral models is the Grouped Query Attention (GQA), which boosts the inference time by lowering the number of attention computations compared to standard full attention. Another impressive feature is the Sliding Window Attention (SWA), which enables Mistral models to handle longer text sequences with minimal memory usage. These architectural breakthroughs make Mistral models highly efficient and powerful.

Improvements over Predecessors 

Mistral Large is an innovator and trailblazer in the AI industry. It bridges the gap between pioneering research and real-world solutions. Mistral Large improves upon its predecessors, Mistral Small, Mistral of experts, and size-wise Mistral 7B, Mistral 8B, in terms of reasoning capabilities and multilingual proficiency. It excels in understanding and processing complex information, such as long documents, multiple sources, or ambiguous queries. It also adapts to different languages and contexts, such as formal or informal, technical or conversational, or domain-specific or general. 

Some of the improvements that Mistral Large offers are:

• Enhanced reasoning and knowledge: Mistral Large can perform complex reasoning and inference tasks, such as answering questions, solving problems, or explaining concepts. It can also access and integrate a large and diverse knowledge base, such as Wikipedia, news articles, or scientific papers.
• Improved code and math: Mistral Large can generate, review, and comment on code and math with high accuracy and quality. It can also handle various coding and math languages.
• Expanded multilingualism and translation: Mistral Large can handle more languages and dialects than its predecessors. It can also translate between any pair of languages with high accuracy and fluency.

Novel Use Cases 

Mistral Large enables novel use cases that were not possible or feasible before. Its precise information recall from large documents allows users to find the exact information they need from a vast amount of text. Its precise instruction-following enables developers to design their moderation policies and rules for their content or platforms. Some of the novel use cases that Mistral Large enables are:

• Document analysis and summarization: Mistral Large can analyze and summarize long and complex documents, such as legal contracts, research papers, or business reports. It can extract the key points, insights, and conclusions from the text and present them in a concise and clear way.
• Content moderation and filtering: Mistral Large can moderate and filter content based on user-defined criteria, such as keywords, topics, or sentiments. It can also flag or remove inappropriate or harmful content, such as spam, hate speech, or fake news.
• Content generation and personalization: Mistral Large can generate and personalize content for different purposes and audiences, such as blogs, newsletters, or social media posts. It can also adapt its tone, style, and language to the user’s preferences and needs.

Model Use 

Mistral Large is available through Models-as-a-Service (MaaS) that offers API-based access and token-based billing for LLMs. Developers can provision an API endpoint in a matter of seconds and try out the model in the Azure AI Studio playground or use it with popular LLM app development tools like Azure AI prompt flow and LangChain. 

Some of the steps to use Mistral Large are:

1. Sign up for a Mistral AI account and subscribe to Mistral Large.
2. Create an API key and endpoint for Mistral Large.
3. Send requests to the endpoint with your inputs and parameters.
4. Receive responses from the endpoint with your outputs and metrics.

Conclusion 

Mistral Large is a significant advancement in the field of AI. Its unique features and capabilities make it a valuable asset for a wide range of applications. As we look forward to future developments, Mistral Large stands as a testament to the potential of AI to transform our world.

Source 
Mistral blog : https://mistral.ai/news/mistral-large/
Endpoints: https://docs.mistral.ai/platform/endpoints/
Microsoft blog:  https://techcommunity.microsoft.com/t5/ai-machine-learning-blog/mistral-large-mistral-ai-s-flagship-llm-debuts-on-azure-ai/ba-p/4066996