Best Large Language Models for Groq

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.

OpenAI's mission, which is to ensure artificial general intelligence (AGI), benefits all people. This refers to highly autonomous systems that outperform humans in most economically valuable work. While we will try to build safe and useful AGI, we will also consider our mission accomplished if others are able to do the same. Our API can be used to perform any language task, including summarization, sentiment analysis and content generation. You can specify your task in English or use a few examples. Our constantly improving AI technology is available to you with a simple integration. These sample completions will show you how to integrate with the API.

DeepSeek-R1 is a cutting-edge open-source reasoning model crafted by DeepSeek, designed to compete with leading models like OpenAI's o1. Available through web platforms, applications, and APIs, it excels in tackling complex challenges such as mathematics and programming. With outstanding performance on benchmarks like the AIME and MATH, DeepSeek-R1 leverages a mixture of experts (MoE) architecture, utilizing 671 billion total parameters while activating 37 billion parameters per token for exceptional efficiency and accuracy. This model exemplifies DeepSeek’s dedication to driving advancements in artificial general intelligence (AGI) through innovative and open source solutions.

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.

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.

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.

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.

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

With our enterprise Gen AI stack you can go beyond your imagination. You can instantly offload manual tasks and give them to powerful assistants. The sky is the limit. For enterprises that place data security first, fine-tune generative AI models and deploy them on your own cloud securely.