Mistral Medium

Mistral AI offers advanced large language models (LLMs) designed for complex tasks such as text generation, multilingual reasoning, and code generation. These models are engineered to provide high-performance natural language processing capabilities for a variety of applications in both commercial and research environments.

Key features:
- Multilingual Proficiency: Fluent in English, French, Spanish, German, and Italian, with nuanced understanding of grammar and cultural context.
- 32K Token Context Window: Allows for precise information recall from extensive documents.
- Instruction Following and Function Calling: Enables developers to design moderation policies and integrate with various tools.
- Top-tier Reasoning Capabilities: Excels in complex reasoning tasks, including text understanding, transformation, and code generation.
- Sparse Mixture of Experts (MoE) Architecture: Uses up to 141B parameters but only 39B during inference, optimizing for fast, low-cost inference.
- Versatile NLP Tasks: Suitable for chatbots, content generation, and other complex text understanding tasks.
- Optimized for Low Latency: Designed for tasks requiring quick responses, such as classification, customer support, and bulk text generation.
- Cost-Effective Options: Lower latency and cost compared to larger models for simpler tasks.

How it works:
1. Users interact with Mistral AI models through La Plateforme, Mistral's infrastructure in Europe.
2. Models are also available through Azure AI Studio and Azure Machine Learning.
3. For sensitive use cases, models can be self-deployed in user environments with access to model weights.
4. Users can leverage the models for tasks such as text generation, code generation, and multilingual content creation.

Integrations:
Azure, Amazon Bedrock, NVIDIA NIM Microservices

Use of AI:
Mistral AI's models are part of NVIDIA's AI Foundation models, optimized for latency and throughput using NVIDIA TensorRT-LLM. The models are available in .nemo format, allowing for customization using techniques like SFT, LoRA, RLFH, and SteerLM.

AI foundation model:
Mistral AI's foundation models include Mistral Large, Mixtral 8x22B, and Mistral Small. These models are designed to handle a wide range of natural language processing tasks with varying levels of complexity and resource requirements.

Target users:
- Developers building applications requiring advanced text generation, multilingual capabilities, and code generation
- Enterprises needing scalable AI solutions for customer support, content generation, and data extraction
- Researchers conducting studies in natural language processing and AI

How to access:
Mistral AI's models are accessible through a web app on La Plateforme, cloud services on Azure and Amazon Bedrock, and API endpoints for integration into various applications. Some models are available under the Apache 2 license for open-source use.

Model variants:
- Mistral Large: Flagship model with multilingual proficiency and a 32K token context window
- Mixtral 8x22B: Utilizes a Sparse Mixture of Experts architecture for efficient processing
- Mistral Small: Optimized for low latency and cost-effective performance on simpler tasks