NEWS · MODELS · #215
Beyond price per token: choosing the right OpenAI model on Amazon Bedrock
An AWS Machine Learning blog post argues that comparing models by dollars per million tokens misses production costs tied to outcomes, and shares an open-source benchmarking harness that measures cost per correct answer, agent trajectory cost, and rubric-graded deliverable quality across OpenAI models on Amazon Bedrock.
KEY POINTS
- An AWS Machine Learning blog post argues that comparing models by dollars per million tokens misses production costs tied to outcomes, and shares an open-source benchmarking harness that measures cost per correct answer, agent trajectory cost, and rubric-graded deliverable quality across OpenAI models on Amazon Bedrock.
- Provides a practical, outcome-oriented benchmarking tool and metrics for selecting OpenAI models on Bedrock, which can change cost/quality trade-offs in production.
- Beyond the price per token: Choosing the right OpenAI model on Amazon Bedrock for your workload
WHY IT MATTERS
Provides a practical, outcome-oriented benchmarking tool and metrics for selecting OpenAI models on Bedrock, which can change cost/quality trade-offs in production.