Today, we announce that the Pixtral Large 25.02 model is now available in Amazon Bedrock as a fully managed, serverless offering. AWS is the first major cloud provider to deliver Pixtral Large as a fully managed, serverless model.
Working with large foundation models (FMs) often requires significant infrastructure planning, specialized expertise, and ongoing optimization to handle the computational demands effectively. Many customers find themselves managing complex environments or making trade-offs between performance and cost when deploying these sophisticated models.
The Pixtral Large model, developed by Mistral AI, represents their first multimodal model that combines advanced vision capabilities with powerful language understanding. A 128K context window makes it ideal for complex visual reasoning tasks. The model delivers exceptional performance on key benchmarks including MathVista, DocVQA, and VQAv2, demonstrating its effectiveness across document analysis, chart interpretation, and natural image understanding.
One of the most powerful aspects of Pixtral Large is its multilingual capability. The model supports dozens of languages including English, French, German, Spanish, Italian, Chinese, Japanese, Korean, Portuguese, Dutch, and Polish, making it accessible to global teams and applications. It’s also trained on more than 80 programming languages including Python, Java, C, C++, JavaScript, Bash, Swift, and Fortran, providing robust code generation and interpretation capabilities.
Developers will appreciate the model’s agent-centric design with built-in function calling and JSON output formatting, which simplifies integration with existing systems. Its strong system prompt adherence improves reliability when working with Retrieval Augmented Generation (RAG) applications and large context scenarios.
With Pixtral Large in Amazon Bedrock, you can now access this advanced model without having to provision or manage any infrastructure. The serverless approach lets you scale usage based on actual demand without upfront commitments or capacity planning. You pay only for what you use, with no idle resources.
Cross-Region inference
Pixtral Large is now available in Amazon Bedrock across multiple AWS Regions through cross-Region inference.
With Amazon Bedrock cross-Region inference, you can access a single FM across multiple geographic Regions while maintaining high availability and low latency for global applications. For example, when a model is deployed in both European and US Regions, you can access it through Region-specific API endpoints using distinct prefixes: eu.model-id for European Regions and us.model-id for US Regions . This approach enables Amazon Bedrock to route inference requests to the geographically closest endpoint, reducing latency while helping to meet regulatory compliance by keeping data processing within desired geographic boundaries. The system automatically handles traffic routing and load balancing across these Regional deployments, providing seamless scalability and redundancy without requiring you to keep track of individual Regions where the model is actually deployed.
See it in action
As a developer advocate, I’m constantly exploring how our newest capabilities can solve real problems. Recently, I had a perfect opportunity to test the new multimodal capabilities in the Amazon Bedrock Converse API when my daughter asked for help with her physics exam preparation.
Last weekend, my kitchen table was covered with practice exams full of complex diagrams, force vectors, and equations. My daughter was struggling with conceptualizing how to approach these problems. That’s when I realized this was the perfect use case for the multimodal capabilities we’d just launched. I snapped photos of a particularly challenging problem sheet containing several graphs and mathematical notation, then used the Converse API to create a simple application that could analyze the images. Together, we uploaded the physics exam materials and asked the model to explain the solution approach.
What happened next impressed both of us—the model interpreted the diagrams, recognized the french language and the mathematical notation, and provided a step-by-step explanation of how to solve each problem. As we asked follow-up questions about specific concepts, the model maintained context across our entire conversation, creating a tutoring experience that felt remarkably natural.
The model uses the language of the question to respond. After a thoughtful analysis, it says that the correct answer is f_c > f_a > f_b (and it is right!)
The beauty of this interaction was how seamlessly the Converse API handled the multimodal inputs. As a builder, I didn’t need to worry about the complexity of processing images alongside text—the API managed that complexity and returned structured responses that my simple application could present directly to my daughter.
Here is the code I wrote. I used the Swift programming language, just to show that Python is not the only option you have 
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And the result in the app is stunning.
By the time her exam rolled around, she felt confident and prepared—and I had a compelling real-world example of how our multimodal capabilities in Amazon Bedrock can create meaningful experiences for users.
Get started today
The new model is available through these Regional API endpoints: US East (Ohio, N. Virginia), US West (Oregon), and Europe (Frankfurt, Ireland, Paris, Stockholm). This Regional availability helps you meet data residency requirements while minimizing latency.
You can start using the model through either the AWS Management Console or programmatically through the AWS Command Line Interface (AWS CLI) and AWS SDK using the model ID mistral.pixtral-large-2502-v1:0.
This launch represents a significant step forward in making advanced multimodal AI accessible to developers and organizations of all sizes. By combining Mistral AI’s cutting-edge model with AWS serverless infrastructure, you can now focus on building innovative applications without worrying about the underlying complexity.
Visit the Amazon Bedrock console today to start experimenting with Pixtral Large 25.02 and discover how it can enhance your AI-powered applications.
— seb
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