AWS re:Invent 2025 - Mastering model choice: The 3-step Amazon Bedrock advantage (AIM391)

Mastering Model Choice: The 3-Step Amazon Bedrock Advantage

Overview

• Customers are overwhelmed by the sheer number of AI models available, with 2.19 million public models in HuggingFace alone.
• Choosing the right model for a specific use case is a significant challenge, with consequences for time, cost, and organizational momentum.
• Amazon Bedrock provides a solution to help developers focus on building applications while AWS handles model selection, optimization, and deployment.

The 3-Step Framework

1. Identify Candidate Models:

   • Filter models by modality (text, image, video, etc.) to match the use case requirements.
   • Leverage benchmarks and metrics like the Anthropic Intelligence Index to quickly compare model performance.
   • Consider specialized model categories like reasoning models, science/math models, and domain-specific models.

2. Evaluate Models:

   • Create a "golden data set" of representative use cases and ground truth answers.
   • Use programmatic evaluation, human evaluation, and language model-based evaluation to assess model performance.
   • Measure key metrics like quality, speed, and cost-efficiency.
   • Continuously monitor and update the golden data set as requirements change.

3. Optimize the Solution:

   • Consider using a combination of models, with each specialized for a specific task.
   • Fine-tune or distill models to improve performance for the target use case.
   • Optimize the inference request routing to balance cost, latency, and accuracy requirements.
   • Leverage Amazon Bedrock features like inference tiers and custom model import to customize the deployment.

Real-World Example: Coin Market Cap

• Coin Market Cap, a leading cryptocurrency data platform, has built a comprehensive AI-powered solution using the 3-step framework.
• They use specialized models for different tasks, such as sentiment extraction, planning, data retrieval, summarization, and language-to-ID translation.
• Coin Market Cap leverages Amazon Bedrock for inference, knowledge retrieval, and security, while also partnering closely with AWS for technical support and benchmarking.
• The company has scaled to process trillions of LLM tokens per day, serving millions of users with personalized AI-powered experiences.

Key Takeaways

• Choosing the right AI models is critical for successful application development, but can be a significant challenge.
• Amazon Bedrock provides a comprehensive solution, including a 3-step framework for identifying, evaluating, and optimizing models.
• Real-world examples like Coin Market Cap demonstrate the power of this approach, enabling scalable, cost-effective, and high-performing AI applications.
• Continuous model evaluation, optimization, and integration with cloud services like Amazon Bedrock are key to delivering successful AI-powered solutions.