Introduction

As we know, Mistral AI is one of the buzziest companies in the AI ecosystem. Established in April 2023, the organization was founded by former Meta, OpenAI, and Google DeepMind researchers, namely Arthur Mensch, Timothée Lacroix, and Guillaume Lample.

Recently, it has gained traction in the LLM trend. But why is Mistral in the limelight? This Paris-based AI startup plans to build an alternative to OpenAI and Anthropic. Mistral AI has announced Mistral Large, the latest model from Mistral.

Interestingly, it outperforms Mistral Medium, boasting the ability to handle 32k context tokens. It has native English, French, Spanish, German, and Italian fluency. Intriguing right? It doesn’t stop here! Additionally, Mistral AI has also announced – Mistral Small has been upgraded to a model that surpasses the performance of Mixtral 8x7B while maintaining faster processing speeds.

Lastly, Mistral is unveiling Le Chat, a chat interface currently in beta, built on top of their models. But is Mistral Large just another pretty face, or does it offer genuine advantages for multiple users of different domains? Let’s delve into the model’s capabilities, compare it to other models (OpenAI Vs Mistral AI), and explore its potential impact on our coding endeavors.

Mistral AI: An Overview

Based in France, Mistral AI has long served as a standard-bearer for the open-source AI movement. However, amid the previous year, the emergence of Mistral marked a significant shift. Mistral means – Strong wind blowing from France. Likewise, it is taking the world of AI by storm. Before Mistral, Meta Llama had been unquestionably dominant, capturing the spotlight in the entire open-source conversation. A vast community of developers was actively contributing and building upon its foundations. With the introduction of Mistral (a 2 billion dollar firm), a noticeable shift occurred, redirecting attention and influence within the open-source landscape. Mistral drew considerable attention, gradually becoming a focal point in the open-source community.

Nowadays, large language models (LLMs) are a bustling marketplace, with established vendors and new challengers vying for your attention. As learners, we constantly seek tools to streamline workflow and boost productivity. So, when a new LLM named Mistral Large struts into the market, claiming to be a worthy alternative to the popular ChatGPT, it piques our interest.

Microsoft Mistral AI deal – EU got worried (Latest)

Microsoft’s $16-million multi-year agreement with Mistral AI has raised concerns in the European Union (EU) over potential concentration of power. It looks like Satya Nadela wants to put all eggs in all AI baskets.

The deal – Microsoft – Mistral aims to:

1. Address Supercomputing Infrastructure: Microsoft plans to provide Mistral with state-of-the-art performance and scalability for training new AI models through the Azure AI supercomputing infrastructure.
2. Scale to Market: Mistral AI’s premium models will be accessible to customers via Models as a Service (MaaS) through Azure AI Studio and the Azure Machine Learning model catalog, facilitated by the collaboration between Microsoft and Mistral.
3. AI Research and Development: The two firms will investigate opportunities for cooperation in developing models tailored for specific purposes, catering to selected clients, which may include addressing the workloads of the European public sector.

The EU is examining the partnership amid worries about competition in the generative AI market, particularly given Microsoft’s past scrutiny for investments in OpenAI. Mistral’s lobbying for looser AI regulations in the EU has also sparked questions about its motivations in partnering with a tech giant. The startup announced a similar partnership with Google Cloud in December 2023. Let’s compare – OpenAI Vs. Mistral AI.

OpenAI Vs. Mistral AI

Mistral AI offers open-source alternatives to large language model platforms and has gained attention with rapid innovation and significant funding. If you compare OpenAI Vs. Mistral AI – The OpenAI cost is close to $100 million, and Mistral AI’s cost is around $22 million. Moreover, French President Macron said this is a “France Genius”.

Mistral AI stands out with its open-source model, a key advantage over closed models like OpenAI. Mistral AI’s commitment to an open-source model is a significant differentiator in the rapidly evolving field of artificial intelligence. By opting for an open-source approach, Mistral AI fosters transparency and encourages collaboration within the AI community. Also, Nvidia and Salesforce fund Mistral AI, and Amazon has signed a deal with the company. But the real question is: Can Mistral AI take on OpenAI? Let’s find out.

Also Watch this Video you will Find the Comparision about Mistral Large vs Chatgpr vs Gemini : Which is best AI tool to use in this Video:

Mistral Large capacities

To comprehend its capacities, we will compare them with other LLM models.

Mistral Large: Boasting Reasoning and Affordability

Firstly, let’s understand – What exactly is Mistral Large?

What is Mistral Large?

Mistral Large, Mistral AI’s flagship model, boasts unparalleled reasoning capacities and is now accessible on Azure, marking their first distribution partnership. This cutting-edge language model, available through la Plateforme, also excels in top-tier reasoning capabilities. Its versatility extends to handling complex multilingual reasoning tasks, such as text comprehension, transformation, and code generation. It ranks as the world’s second-best API-available model globally, following GPT-4:

Mistral Large is positioned as a competitor to established LLMs like ChatGPT and Claude 2. Its key selling point lies in its purportedly superior reasoning capabilities. Mistral AI claims the model excels in tasks requiring logical deduction, information retrieval, and question answering.

Another potential advantage is its price point. Compared to its competitors, it boasts a significantly lower cost. It comes at a 20% lower cost than the latest GPT iteration, GPT-4 Turbo. In contrast, GPT-4 Turbo, featuring a 128k-token context window, is priced at $10 per million input tokens and $30 per million output tokens. Therefore, it is 20% more affordable than GPT-4 Turbo. It’s important to note that the AI industry experiences rapid changes, with companies frequently updating their pricing structures. We can comprehend that the equivalent service on OpenAI’s GPT-4 can cost up to five times more.

Mistral Large’s Multi-lingual Capacities

Possessing inherent multi-lingual capabilities, it significantly surpasses LLaMA 2 70B on various benchmarks such as HellaSwag, Arc Challenge, and MMLU, particularly excelling in evaluations conducted in French, German, Spanish, and Italian languages.

Mistral Large’s Maths & Coding Capabilities

It demonstrates exceptional proficiency in coding and mathematical tasks, showcasing top-notch performance. The table below details the model’s performance across widely recognized benchmarks, offering a comprehensive evaluation of its coding and math capabilities compared to other leading LLM models.

Beyond Benchmarks: Real-World Performance Matters

While Mistral AI throws around impressive benchmark results, real-world performance truly matters to the users. We need to see how the model fares in tackling the everyday challenges of the user. Independent evaluations and head-to-head comparisons with established LLMs on various coding-related tasks are crucial for making informed decisions.

Remember, the LLM landscape is constantly evolving. Today’s top performer might not hold the crown tomorrow. Continuous development and refinement are essential for any LLM to stay ahead of the curve.

Currently, it is accessible on both La Plateforme and Azure. It is also featured on Mistral’s beta assistant demonstrator, Le Chat.

Le Chat: A User-Friendly Bridge to Mistral Large

Alongside Mistral Large, Mistral AI introduced Le Chat, their consumer-facing chatbot. Le Chat is a user-friendly interface that allows coders to interact with the powerful AI model without getting bogged down in technical complexities.

First, you must log on to the Le Chat platform to access it.

After creating the account, you will be asked to wait in the queue. ( It usually takes around 1-2 hours).

Here is the interface of Le Chat Mistral:

Currently, the service is free, and users can select from three distinct models: Mistral Small, Mistral Large, and a concise prototype named Mistral Next. It is important to highlight that Le Chat does not have internet access during usage.

• Large – Top reasoning capabilities
• Next – Prototype model with extra concision
• Small – Fast and cost-effective

Choose as per your requirements.

Let’s give Le Chat a prompt: Give me a Python code for bubble sorting

Here is the output with the description:

Ethical Considerations: A Shared Responsibility

As LLMs like Mistral Large become more powerful and accessible, ethical considerations become paramount. We must ensure these models are used responsibly and ethically. Issues like bias, misinformation, and potential misuse require careful attention and the development of responsible AI practices.

The Future of LLMs: Collaboration is Key

The future of LLMs is likely to be collaborative, with different models working together to complement each other’s strengths and address weaknesses. Mistral Large’s emergence adds another player to the mix, potentially fostering a more competitive and innovative LLM landscape. While its long-term impact remains to be seen, its presence serves as a reminder of the dynamic nature of this field and the exciting possibilities it holds for the future of coding.

So, is it a viable alternative to ChatGPT?

Like most things in technology, the answer is “it depends.” Both models have their strengths and weaknesses. While its affordability and reasoning capabilities are enticing, real-world performance and ongoing development remain crucial. Ultimately, the best LLM for you will depend on your specific needs, budget, and coding style.

However, one thing is certain: the arrival of Mistral Large injects a dose of healthy competition into the LLM market, ultimately benefiting the coders. With more options to choose from and continuous innovation, we can expect a future where LLMs become increasingly powerful and valuable partners in coding endeavors. I have also provided the output of both models using the same prompt:

Pricing of Mistral AI Models

Here are the pricing and rate limits of different models by Mistral AI:

Pricing of Chat Completions API

Pricing of Embeddings API

Conclusion

In conclusion, Mistral Large offers a compelling alternative to ChatGPT for developers and coders looking to enhance their AI capabilities. With its advanced architecture, improved accuracy, and enhanced customization options, it is quickly becoming popular for those seeking a powerful and cost-effective AI solution. As the field of artificial intelligence continues to evolve, models like Mistral Large will play a crucial role in shaping the future of AI technology.

You can also read: From GPT to Mistral-7B: The Exciting Leap Forward in AI Conversations.