AWS announces AWS-bench, an open-source benchmark for AI agents on AWS
{"data":{"items":[{"fields":{"nofollow":"0","noindex":"0","postBody":"<p>Today, AWS announces a research preview of aws-bench, an open-source benchmark that measures how accurately and efficiently AI agents complete real-world AWS tasks. Researchers and model providers can use aws-bench to improve foundation model performance on AWS tasks, improve agent harnesses, and track improvement progress. The release includes an easy-to-use CLI tool to instantiate testing environments, execute and score evaluation runs, and reset resource state.<br>\n<br>\naws-bench is available now on <a href=\"https://github.com/aws-bench/aws-bench\">GitHub</a>.
- ▪{"data":{"items":[{"fields":{"nofollow":"0","noindex":"0","postBody":"<p>Today, AWS announces a research preview of aws-bench, an open-source benchmark that measures how accurately and efficiently AI agents complete real-world AWS tasks.
- ▪Researchers and model providers can use aws-bench to improve foundation model performance on AWS tasks, improve agent harnesses, and track improvement progress.
- ▪The release includes an easy-to-use CLI tool to instantiate testing environments, execute and score evaluation runs, and reset resource state.<br>\n<br>\naws-bench is available now on <a href=\"https://github.com/aws-bench/aws-bench\">GitHu
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{"data":{"items":[{"fields":{"nofollow":"0","noindex":"0","postBody":"<p>Today, AWS announces a research preview of aws-bench, an open-source benchmark that measures how accurately and efficiently AI agents complete real-world AWS tasks. Model providers and AI researchers building agents that operate on AWS infrastructure need an objective, reproducible way to measure performance and diagnose failures. aws-bench provides a public suite of test cases derived from analysis of real AWS usage, including investigation, troubleshooting, and infrastructure creation tasks.<br>\n<br>\nEach test case pairs a natural-language query with a defined cloud resource state and a ground-truth answer, so you can score any agent or model on a consistent, verifiable basis.
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