Mistral AI’s Mistral Large 2 (24.07) foundation model (FM) is now generally available in Amazon Bedrock. Mistral Large 2 is the newest version of Mistral Large, and according to Mistral AI offers significant improvements across multilingual capabilities, math, reasoning, coding, and much more.
In this post, we discuss the benefits and capabilities of this new model with some examples.
Overview of Mistral Large 2
Mistral Large 2 is an advanced large language model (LLM) with state-of-the-art reasoning, knowledge, and coding capabilities according to Mistral AI. It is multi-lingual by design, supporting dozens of languages, including English, French, German, Spanish, Italian, Chinese, Japanese, Korean, Portuguese, Dutch, Polish, Arabic, and Hindi. Per Mistral AI, a significant effort was also devoted to enhancing the model’s reasoning capabilities. One of the key focuses during training was to minimize the model’s tendency to hallucinate, or generate plausible-sounding but factually incorrect or irrelevant information. This was achieved by fine-tuning the model to be more cautious and discerning in its responses, making sure it provides reliable and accurate outputs. Additionally, the new Mistral Large 2 is trained to acknowledge when it can’t find solutions or doesn’t have sufficient information to provide a confident answer.
According to Mistral AI, the model is also proficient in coding, trained on over 80 programming languages such as Python, Java, C, C++, JavaScript, Bash, Swift, and Fortran. With its best-in-class agentic capabilities, it can natively call functions and output JSON, enabling seamless interaction with external systems, APIs, and tools. Additionally, Mistral Large 2 (24.07) boasts advanced reasoning and mathematical capabilities, making it a powerful asset for tackling complex logical and computational challenges.
Mistral Large 2 also offers an increased context window of 128,000 tokens. At the time of writing, the model (mistral.mistral-large-2407-v1:0) is available in the us-west-2
AWS Region.
Get started with Mistral Large 2 on Amazon Bedrock
If you’re new to using Mistral AI models, you can request model access on the Amazon Bedrock console. For more details, see Manage access to Amazon Bedrock foundation models.
To test Mistral Large 2 on the Amazon Bedrock console, choose Text or Chat under Playgrounds in the navigation pane. Then choose Select model and choose Mistral as the category and Mistral Large 24.07 as the model.
By choosing View API request, you can also access the model using code examples in the AWS Command Line Interface (AWS CLI) and AWS SDKs. You can use model IDs such as mistral.mistral-large-2407-v1:0
, as shown in the following code:
In the following sections, we dive into the capabilities of Mistral Large 2.
Increased context window
Mistral Large 2 supports a context window of 128,000 tokens, compared to Mistral Large (24.02), which had a 32,000-token context window. This larger context window is important for developers because it allows the model to process and understand longer pieces of text, such as entire documents or code files, without losing context or coherence. This can be particularly useful for tasks like code generation, documentation analysis, or any application that requires understanding and processing large amounts of text data.
Generating JSON and tool use
Mistral Large 2 now offers a native JSON output mode. This feature allows developers to receive the model’s responses in a structured, easy-to-read format that can be readily integrated into various applications and systems. With JSON being a widely adopted data exchange standard, this capability simplifies the process of working with the model’s outputs, making it more accessible and practical for developers across different domains and use cases. To learn more about how to generate JSON with the Converse API, refer to Generating JSON with the Amazon Bedrock Converse API.
To generate JSON with the Converse API, you need to define a toolSpec
. In the following code, we present an example for a travel agent company that will take passenger information and requests and convert them to JSON:
We get the following response:
Mistral Large 2 was able to correctly take our user query and convert the appropriate information to JSON.
Mistral Large 2 also supports the Converse API and tool use. You can use the Amazon Bedrock API to give a model access to tools that can help it generate responses for messages that you send to the model. For example, you might have a chat application that lets users find the most popular song played on a radio station. To answer a request for the most popular song, a model needs a tool that can query and return the song information. The following code shows an example for getting the correct train schedule:
We get the following response:
Mistral Large 2 was able to correctly identify the shinkansen tool and demonstrate its use.
Multilingual support
Mistral Large 2 now supports a large number of character-based languages such as Chinese, Japanese, Korean, Arabic, and Hindi. This expanded language support allows developers to build applications and services that can cater to users from diverse linguistic backgrounds. With multilingual capabilities, developers can create localized UIs, provide language-specific content and resources, and deliver a seamless experience for users regardless of their native language.
In the following example, we translate customer emails generated by the author into different languages such as Hindi and Japanese:
We get the following response:
Coding tasks
Mistral Large 2 has been trained on over 80 coding languages, including popular ones like Python, Java, C, C++, JavaScript, and Bash, as well as more specialized languages such as Swift and Fortran. This comprehensive language support empowers developers to tackle a wide range of coding tasks and projects across various domains and platforms. Whether you’re working on web development, mobile applications, scientific computing, or system programming, Mistral Large 2 can assist you with code generation, debugging, refactoring, and other coding-related tasks. For example, the following code requests the model to generate a Python function:
We get the following response:
Conclusion
Mistral AI’s Mistral Large 2 FM is now available on Amazon Bedrock in the US West (Oregon) Region. To get started with Mistral Large 2 in Amazon Bedrock, visit the Amazon Bedrock console.
Interested in diving deeper? Check out the Mistral-on-AWS repo. For more information about Mistral AI on Amazon Bedrock, refer to Mistral AI models now available on Amazon Bedrock.
About the Authors
Niithiyn Vijeaswaran is a Solutions Architect at AWS. His area of focus is generative AI and AWS AI Accelerators. He holds a Bachelor’s degree in Computer Science and Bioinformatics. Niithiyn works closely with the Generative AI GTM team to enable AWS customers on multiple fronts and accelerate their adoption of generative AI. He’s an avid fan of the Dallas Mavericks and enjoys collecting sneakers.
Armando Diaz is a Solutions Architect at AWS. He focuses on generative AI, AI/ML, and Data Analytics. At AWS, Armando helps customers integrating cutting-edge generative AI capabilities into their systems, fostering innovation and competitive advantage. When he’s not at work, he enjoys spending time with his wife and family, hiking, and traveling the world.
Preston Tuggle is a Sr. Specialist Solutions Architect working on generative AI.