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Mistral AI is an advanced artificial intelligence company focused on open-source generative AI solutions. Offering adaptable, enterprise-level AI tools, the company enables deployment across cloud, on-premises, edge, and device-based environments. Key offerings include "Le Chat," a multilingual AI assistant designed for enhanced efficiency in both professional and personal settings, and "La Plateforme," a development platform for building and integrating AI-powered applications. With a strong emphasis on transparency and innovation, Mistral AI continues to drive progress in open-source AI and contribute to shaping AI policy.

GPT-4 (Generative Pretrained Transformer 4) a large-scale, unsupervised language model that is yet to be released. GPT-4, which is the successor of GPT-3, is part of the GPT -n series of natural-language processing models. It was trained using a dataset of 45TB text to produce text generation and understanding abilities that are human-like. GPT-4 is not dependent on additional training data, unlike other NLP models. It can generate text and answer questions using its own context. GPT-4 has been demonstrated to be capable of performing a wide range of tasks without any task-specific training data, such as translation, summarization and sentiment analysis.

Mistral 7B is a cutting-edge 7.3-billion-parameter language model designed to deliver superior performance, surpassing larger models like Llama 2 13B on multiple benchmarks. It leverages Grouped-Query Attention (GQA) for optimized inference speed and Sliding Window Attention (SWA) to effectively process longer text sequences. Released under the Apache 2.0 license, Mistral 7B is openly available for deployment across a wide range of environments, from local systems to major cloud platforms. Additionally, its fine-tuned variant, Mistral 7B Instruct, excels in instruction-following tasks, outperforming models such as Llama 2 13B Chat in guided responses and AI-assisted applications.

Codestral Mamba is a Mamba2 model that specializes in code generation. It is available under the Apache 2.0 license. Codestral Mamba represents another step in our efforts to study and provide architectures. We hope that it will open up new perspectives in architecture research. Mamba models have the advantage of linear inference of time and the theoretical ability of modeling sequences of unlimited length. Users can interact with the model in a more extensive way with rapid responses, regardless of the input length. This efficiency is particularly relevant for code productivity use-cases. We trained this model with advanced reasoning and code capabilities, enabling the model to perform at par with SOTA Transformer-based models.

Grok is a computer program based on the Hitchhiker’s Guide to the galaxy. It can answer virtually any question and, much harder, it can even suggest the questions to be asked! Grok is a witty and rebellious way to answer questions. Please don't use this if you dislike humor! Grok has a unique and fundamental advantage in that it can access real-time information about the world through the X platform. It can also answer questions that other AI systems would reject.

Meta AI is our intelligent assistant that allows people to create, connect and get things done. We've integrated Llama 3. Meta AI can be used to code and solve problems, allowing you to see the performance of Llama 3. Llama 3, in 8B or 70B, will give you the flexibility and capabilities you need to create your ideas, whether you're creating AI-powered agents or other applications. We've updated our Responsible Use Guide (RUG), to provide the most comprehensive and up-to-date information on responsible development using LLMs. Our system-centric approach includes updates for our trust and security tools, including Llama Guard 2 optimized to support MLCommons' newly announced taxonomy, code shield and Cybersec Evaluation 2.

We are proud to introduce Codestral, the first code model we have ever created. Codestral is a generative AI model that is open-weight and specifically designed for code generation. It allows developers to interact and write code using a shared API endpoint for instructions and completion. It can be used for advanced AI applications by software developers as it is able to master both code and English. Codestral has been trained on a large dataset of 80+ languages, including some of the most popular, such as Python and Java. It also includes C, C++ JavaScript, Bash, C, C++. It also performs well with more specific ones, such as Swift and Fortran. Codestral's broad language base allows it to assist developers in a variety of coding environments and projects.

Mistral Large is a state-of-the-art language model developed by Mistral AI, designed for advanced text generation, multilingual reasoning, and complex problem-solving. Supporting multiple languages, including English, French, Spanish, German, and Italian, it provides deep linguistic understanding and cultural awareness. With an extensive 32,000-token context window, the model can process and retain information from long documents with exceptional accuracy. Its strong instruction-following capabilities and native function-calling support make it an ideal choice for AI-driven applications and system integrations. Available via Mistral’s platform, Azure AI Studio, and Azure Machine Learning, it can also be self-hosted for privacy-sensitive use cases. Benchmark results position Mistral Large as one of the top-performing models accessible through an API, second only to GPT-4.

Mistral NeMo, our new best small model. A state-of the-art 12B with 128k context and released under Apache 2.0 license. Mistral NeMo, a 12B-model built in collaboration with NVIDIA, is available. Mistral NeMo has a large context of up to 128k Tokens. Its reasoning, world-knowledge, and coding precision are among the best in its size category. Mistral NeMo, which relies on a standard architecture, is easy to use. It can be used as a replacement for any system that uses Mistral 7B. We have released Apache 2.0 licensed pre-trained checkpoints and instruction-tuned base checkpoints to encourage adoption by researchers and enterprises. Mistral NeMo has been trained with quantization awareness to enable FP8 inferences without performance loss. The model was designed for global applications that are multilingual. It is trained in function calling, and has a large contextual window. It is better than Mistral 7B at following instructions, reasoning and handling multi-turn conversation.

Mixtral 8x22B is our latest open model. It sets new standards for performance and efficiency in the AI community. It is a sparse Mixture-of-Experts model (SMoE), which uses only 39B active variables out of 141B. This offers unparalleled cost efficiency in relation to its size. It is fluently bilingual in English, French Italian, German and Spanish. It has strong math and coding skills. It is natively able to call functions; this, along with the constrained-output mode implemented on La Plateforme, enables application development at scale and modernization of tech stacks. Its 64K context window allows for precise information retrieval from large documents. We build models with unmatched cost-efficiency for their respective sizes. This allows us to deliver the best performance-tocost ratio among models provided by the Community. Mixtral 8x22B continues our open model family. Its sparse patterns of activation make it faster than any 70B model.

As a tribute for Archimedes' 2311th birthday, which we celebrate this year, we release our first Mathstral 7B model, designed specifically for math reasoning and scientific discoveries. The model comes with a 32k context-based window that is published under the Apache 2.0 License. Mathstral is a tool we're donating to the science community in order to help solve complex mathematical problems that require multi-step logical reasoning. The Mathstral release was part of a larger effort to support academic project, and it was produced as part of our collaboration with Project Numina. Mathstral, like Isaac Newton at his time, stands on Mistral 7B's shoulders and specializes in STEM. It has the highest level of reasoning in its size category, based on industry-standard benchmarks. It achieves 56.6% in MATH and 63.47% in MMLU. The following table shows the MMLU performance differences between Mathstral and Mistral 7B.

There are now more versions of the open-source AI model that you can refine, distill and deploy anywhere. Choose from 1B or 3B, or build with Llama 3. Llama 3.2 consists of a collection large language models (LLMs), which are pre-trained and fine-tuned. They come in sizes 1B and 3B, which are multilingual text only. Sizes 11B and 90B accept both text and images as inputs and produce text. Our latest release allows you to create highly efficient and performant applications. Use our 1B and 3B models to develop on-device applications, such as a summary of a conversation from your phone, or calling on-device features like calendar. Use our 11B and 90B models to transform an existing image or get more information from a picture of your surroundings.

Mistral AI has introduced two state of the art models for on-device computing, and edge use cases. These models are called "les Ministraux", Ministral 3B, and Ministral 8B. These models are a new frontier for knowledge, commonsense, function-calling and efficiency within the sub-10B category. They can be used for a variety of applications, from orchestrating workflows to creating task workers. Both models support contexts up to 128k (currently 32k for vLLM) and Ministral 8B has a sliding-window attention pattern that allows for faster and more memory-efficient inference. These models were designed to provide a low-latency and compute-efficient solution for scenarios like on-device translators, internet-less intelligent assistants, local analytics and autonomous robotics. Les Ministraux, when used in conjunction with larger languages models such as Mistral Large or other agentic workflows, can also be efficient intermediaries in function-calling.

Mistral AI has introduced "les Ministraux", two advanced models, for on-device computing applications and edge applications. These models are Ministral 3B (the Ministraux) and Ministral 8B (the Ministraux). These models excel at knowledge, commonsense logic, function-calling and efficiency in the sub-10B parameter area. They can handle up to 128k contexts and are suitable for a variety of applications, such as on-device translations, offline smart assistants and local analytics. Ministral 8B has an interleaved sliding window attention pattern that allows for faster and memory-efficient inference. Both models can be used as intermediaries for multi-step agentic processes, handling tasks such as input parsing and task routing and API calls with low latency. Benchmark evaluations show that les Ministraux consistently performs better than comparable models in multiple tasks. Both models will be available as of October 16, 2024. Ministral 8B is priced at $0.1 for every million tokens.

Mistral AI announced a number of key updates on September 17, 2024 to improve the accessibility and performance. They introduced a free version of "La Plateforme", their serverless platform, which allows developers to experiment with and prototype Mistral models at no cost. Mistral AI has also reduced the prices of their entire model line, including a 50% discount for Mistral Nemo, and an 80% discount for Mistral Small and Codestral. This makes advanced AI more affordable for users. The company also released Mistral Small v24.09 - a 22-billion parameter model that offers a balance between efficiency and performance, and is suitable for tasks such as translation, summarization and sentiment analysis. Pixtral 12B is a model with image understanding abilities that can be used to analyze and caption pictures without compromising text performance.

Mixtral 8x7B has open weights and is a high quality sparse mixture expert model (SMoE). Licensed under Apache 2.0. Mixtral outperforms Llama 70B in most benchmarks, with 6x faster Inference. It is the strongest model with an open-weight license and the best overall model in terms of cost/performance tradeoffs. It matches or exceeds GPT-3.5 in most standard benchmarks.

Open source AI model that you can fine-tune and distill anywhere. Our latest instruction-tuned models are available in 8B 70B and 405B version. Our open ecosystem allows you to build faster using a variety of product offerings that are differentiated and support your use cases. Choose between real-time or batch inference. Download model weights for further cost-per-token optimization. Adapt to your application, improve using synthetic data, and deploy on-prem. Use Llama components and extend the Llama model using RAG and zero shot tools to build agentic behavior. Use 405B high-quality data to improve specialized model for specific use cases.

IBM® Granite™ is an AI family that was designed from scratch for business applications. It helps to ensure trust and scalability of AI-driven apps. Granite models are open source and available today. We want to make AI accessible to as many developers as we can. We have made the core Granite Code, Time Series models, Language and GeoSpatial available on Hugging Face, under a permissive Apache 2.0 licence that allows for broad commercial use. Granite models are all trained using carefully curated data. The data used to train them is transparent at a level that is unmatched in the industry. We have also made the tools that we use available to ensure that the data is of high quality and meets the standards required by enterprise-grade applications.

Pixtral Large is Mistral AI’s latest open-weight multimodal model, featuring a powerful 124-billion-parameter architecture. It combines a 123-billion-parameter multimodal decoder with a 1-billion-parameter vision encoder, allowing it to excel at interpreting documents, charts, and natural images while maintaining top-tier text comprehension. With a 128,000-token context window, it can process up to 30 high-resolution images simultaneously. The model has achieved cutting-edge results on benchmarks like MathVista, DocVQA, and VQAv2, outperforming competitors such as GPT-4o and Gemini-1.5 Pro. Available under the Mistral Research License for non-commercial use and the Mistral Commercial License for enterprise applications, Pixtral Large is designed for advanced AI-powered understanding.

Llama 3.3, the latest in the Llama language model series, was developed to push the limits of AI-powered communication and understanding. Llama 3.3, with its enhanced contextual reasoning, improved generation of language, and advanced fine tuning capabilities, is designed to deliver highly accurate responses across diverse applications. This version has a larger dataset for training, refined algorithms to improve nuanced understanding, and reduced biases as compared to previous versions. Llama 3.3 excels at tasks such as multilingual communication, technical explanations, creative writing and natural language understanding. It is an indispensable tool for researchers, developers and businesses. Its modular architecture enables customization in specialized domains and ensures performance at scale.

Watsonx is a new enterprise-ready AI platform that will multiply the impact of AI in your business. The platform consists of three powerful components, including the watsonx.ai Studio for new foundation models, machine learning, and generative AI; the watsonx.data Fit-for-Purpose Store for the flexibility and performance of a warehouse; and the watsonx.governance Toolkit to enable AI workflows built with responsibility, transparency, and explainability. The foundation models allow AI to be fine-tuned to the unique data and domain expertise of an enterprise with a specificity previously impossible. Use all your data, no matter where it is located. Take advantage of a hybrid cloud infrastructure that provides the foundation data for extending AI into your business. Improve data access, implement governance, reduce costs, and put quality models into production quicker.

The next generation of the large language model. This release includes modelweights and starting code to pretrained and fine tuned Llama languages models, ranging from 7B-70B parameters. Llama 1 models have a context length of 2 trillion tokens. Llama 2 models have a context length double that of Llama 1. The fine-tuned Llama 2 models have been trained using over 1,000,000 human annotations. Llama 2, a new open-source language model, outperforms many other open-source language models in external benchmarks. These include tests of reasoning, coding and proficiency, as well as knowledge tests. Llama 2 has been pre-trained using publicly available online data sources. Llama-2 chat, a fine-tuned version of the model, is based on publicly available instruction datasets, and more than 1 million human annotations. We have a wide range of supporters in the world who are committed to our open approach for today's AI. These companies have provided early feedback and have expressed excitement to build with Llama 2

Falcon is a minimalist Python web API Framework for building robust microservices and app backends. The framework is compatible with both ASGI and gevent/meinheld. The Falcon web framework promotes REST architecture. Resource classes implement HTTP handlers to resolve requests and perform transitions. Falcon is a complement to more general Python webframeworks by adding extra reliability, flexibility and performance where you need it. You can use a number of Falcon templates, add-ons and complementary packages in your projects. You can find a few of these on the Falcon Wiki as a start, but you might also want to search PyPI for more resources.

Le Chat is an interactive conversational interface to interact with Mistral AI's models. It is a fun and pedagogical way to learn about Mistral AI. Le Chat can use Mistral Large, Mistral Small, or a prototype called Mistral Next. This model is designed to be concise and brief. Our models are constantly being improved to be as useful as possible and to be as opinionated as we can. However, there is still much to improve! Le Chat's system-level moderation allows you to customize the way you are warned when you push the conversation in a direction where the assistant could produce sensitive or controversial content.

Software is what transforms a vehicle into a smart machine. Open source software stack NVIDIA DRIVE™, enables developers to quickly build and deploy a variety state-of the-art AV applications. This includes perception, localization, mapping, driver monitoring, planning and control, driver monitoring and natural language processing. DRIVE OS, the foundation of the DRIVE SoftwareStack, is the first secure operating system for accelerated computation. It includes NvMedia to process sensor input, NVIDIACUDA®, libraries for parallel computing implementations that are efficient, NVIDIA TensorRT™ for real time AI inference, as well as other tools and modules for accessing hardware engines. NVIDIA DriveWorks®, a SDK that provides middleware functions over DRIVE OS, is essential for autonomous vehicle development. These include the sensor abstraction layer (SAL), sensor plugins, data recorder and vehicle I/O support.

Llama (Large Language Model meta AI) is a state of the art foundational large language model that was created to aid researchers in this subfield. Llama allows researchers to use smaller, more efficient models to study these models. This further democratizes access to this rapidly-changing field. Because it takes far less computing power and resources than large language models, such as Llama, to test new approaches, validate other's work, and explore new uses, training smaller foundation models like Llama can be a desirable option. Foundation models are trained on large amounts of unlabeled data. This makes them perfect for fine-tuning for many tasks. We make Llama available in several sizes (7B-13B, 33B and 65B parameters), and also share a Llama card that explains how the model was built in line with our Responsible AI practices.