Optimize reasoning models like DeepSeek with prompt optimization on Amazon Bedrock

This article discusses how to optimize reasoning models like DeepSeek-R1 using prompt optimization on Amazon Bedrock. Key highlights include:

• DeepSeek-R1 models are known for elaborate thinking styles that can consume many tokens
• Prompt optimization can reduce thinking tokens while maintaining or improving accuracy
• Experiments on the Humanity's Last Exam (HLE) dataset showed promising results:
  • Accuracy improved from 8.75% to 11%
  • Thinking tokens reduced significantly
  • Percentage of thinking completed increased from 80% to 90.3%
• Optimized prompts provide clearer instructions and more structured guidance

The research demonstrates that prompt optimization can make reasoning-intensive AI models more efficient and cost-effective, especially for production environments where computational resources are limited.