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Mistral AI’s Large Model: A Formidable Challenger to GPT-4

Author image - Ayesha
Ayesha Saleem

February 27

In the dynamic world of artificial intelligence, strides in innovation are commonplace. At the forefront of these developments is Mistral AI, a European company emerging as a strong contender in the Large Language Models (LLM) arena with its latest offering: Mistral Large. With capabilities meant to rival industry giants, Mistral AI is poised to leave a significant imprint on the tech landscape.


Features of Mistral AI’s large model


Mistral AI’s new flagship model, codenamed Mistral Large, isn’t just a mere ripple in the AI pond; it’s a technological tidal wave. As we take a look at what sets it apart, let’s compare the main features and capabilities of Mistral AI’s Large model, as detailed in the sources, with those commonly attributed to GPT-4.


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Language support

Mistral Large: Natively fluent in English, French, Spanish, German, and Italian.
GPT-4: is known for supporting multiple languages, but the exact list isn’t specified in the sources.



Mistral Large: Offers different versions, including Mistral Small for lower latency and cost optimization.
GPT-4: Provides various scales of models, but specific details on versions aren’t provided in the sources.


Training and cost

Mistral Large: Charges $8 per million input tokens and $24 per million output tokens.
GPT-4: Mistral Large is noted to be 20% cheaper than GPT-4 Turbo, which suggests GPT-4 would be more expensive.


Performance on benchmarks

Mistral Large: Claims to rank second after GPT-4 on commonly used benchmarks and only marginally outperforms offerings from Google and Meta under the MMLU benchmark.


It is known to be one of the leading models in terms of benchmark performance, but no specific details on benchmark scores are provided in the sources.

Cost to train

Mistral Large: The model reportedly cost less than $22 million to train.
GPT-4: cost over $100 million to develop, according to claims.

Multilingual Abilities

Le Chat supports a variety of languages including English, French, Spanish, German, and Italian 1.

Different Versions

Users can choose between three different models, namely Mistral Small, Mistral Large, and Mistral Next, the latter of which is designed to be brief and concise.

Web Access

Currently, Le Chat does not have the capability to access the internet 1.

Free Beta Access

Le Chat is available in a beta version that is free for users, requiring just a sign-up to use 2.

Planned Enterprise Version

Mistral AI plans to offer a paid version for enterprise clients with features like central billing and the ability to define moderation mechanisms

Please note that this comparison is based on the information provided within the sources, which may not include all features and capabilities of GPT-4 or Mistral Large.


Mistral AI vs. GPT-4: A comparative look


Mistral AI's Large Model Challenger to GPT-4 Dominance
Comparing Mistral AI’s Large Model to GPT-4


Against the backdrop of OpenAI’s GPT-4 stands Mistral Large, challenging the status quo with outstanding features. While GPT-4 shines with its multi-language support and high benchmark performance, Mistral Large offers a competitive edge through:


Affordability: It’s 20% cheaper than GPT-4 Turbo, negotiating cost-savings for AI-powered projects.


Benchmark Performance: Mistral Large competes closely with GPT-4, ranking just behind it while surpassing other tech behemoths in several benchmarks.


Multilingual Prowess: Exceptionally fluent across English, French, Spanish, German, and Italian, Mistral Large breaks language barriers with ease.


Efficiency in Development: Crafted with capital efficiency in mind, Mistral AI invested less than $22 million in training its model, a fraction of the cost incurred by its counterparts.


Commercially Savvy: The model offers a paid API with usage-based pricing, balancing accessibility with a monetized business strategy, presenting a cost-effective solution for developers and businesses.


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Practical applications of Mistral AI’s Large and GPT-4


The applications of both Mistral AI’s Large and GPT-4 sprawl across various industries and use cases, such as:


Natural Language Understanding: Both models demonstrate excellence in understanding and generating human-like text, pushing the boundaries of conversational AI.


Multilingual Support: Business expansion and global communication are facilitated through the multilingual capabilities of both LLMs.


Code Generation: Their ability to understand and generate code makes them invaluable tools for software developers and engineers.


Recommendations for use


As businesses and individuals navigate through the options in large language models, here’s why you might consider each tool:


Choose Mistral AI’s Large: If you’re looking for a cost-effective solution with efficient multilingual support and the flexibility of scalable versions to suit different needs 2.


Opt for GPT-4: Should your project require the prestige and robustness associated with OpenAI’s cutting-edge research and model performance, GPT-4 remains an industry benchmark 3.



Final note


In conclusion, while both Mistral AI’s Large and GPT-4 stand as pioneers in their own right, the choice ultimately aligns with your specific requirements and constraints. With Mistral AI nipping at the heels of OpenAI, the world of AI remains an exciting space to watch.


The march of AI is relentless, and as Mistral AI parallels the giants in the tech world, make sure to keep abreast of their developments, for the choice you make today could redefine your technological trajectory tomorrow.

Author image - Ayesha
Written by Ayesha Saleem
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