Primary sourceAWS Machine Learning Blog
View sourceEvent ·Official first-hand
用 NVIDIA NeMo Switchyard 在 Amazon Bedrock 上按任务路由编程 Agent 请求
这篇教程教你用 AWS CDK 在 Amazon Bedrock 上部署 LiteLLM,并接入 NVIDIA NeMo Switchyard 路由插件,把编程 Agent 的请求动态路由到合适的模型。文中构建一个路由模型组(routed model group),并与单模型基线逐一对比。评估指标是每解决一个任务的成本(cost per solved task),而不是单纯看每 token 的价格,更贴近编程 Agent 实际跑任务的开销。整套方案以 IaC 方式部署,方便团队在自己的 AWS 环境复现并按自身任务集量化路由带来的成本收益。
Current read
编程 Agent 跑任务,真正该看的指标是每解决一个任务花多少钱,不是每 token 单价。这篇教程手把手用 AWS CDK 部署 LiteLLM 加 NVIDIA NeMo Switchyard,把请求路由到 Bedrock 上的不同模型,再和单模型基线比成本。自己搭 Agent 团队、想在强模型和便宜模型之间省钱的开发者可以直接照着抄。
11 sources41° AI heatLast updated 2026/11/13 22:30:12
Evidence
11 sourcesRelated source 1Amazon Science
View sourceRelated source 2LMSYS Org (SGLang)
View sourceRelated source 3Mira Murati (TML)
View sourceRelated source 4Tech in Asia
View sourceRelated source 5vLLM
View sourceRelated source 6Sebastian Raschka
View sourceRelated source 7Latent Space (swyx)
View sourceRelated source 8TestingCatalog
View sourceRelated source 9Decoder
View sourceRelated source 10SambaNova
View sourceConflict check
Dedup data only shows that these sources discuss the same event, not that they agree. There is no structured supporting or refuting evidence yet, so no conflict is inferred automatically.