Reflection AI 发布开源权重模型 Beam，支持在 AWS 部署智能体编程
Introducing Reflection Beam: an open-weight model for agentic coding on AWS
Reflection AI 把自家的智能体编程模型 Beam 开源了，AWS 博客还手把手教你在 SageMaker 上部署，vLLM、SGLang 都能用。
Reflection AI 发布了面向智能体编程和长时程任务的开源权重模型 Beam。用户可通过 Amazon SageMaker JumpStart 一键启动实时端点，也可以用 SageMaker HyperPod Inference 配合 JumpStart、SGLang 或 vLLM 在 Kubernetes 上管理分布式 GPU 推理。文章给出了具体的部署路径，开发者可以自行掌控推理基础设施。
Introducing Reflection Beam: an open-weight model for agentic coding on AWS
Reflection AI's Beam is an open-weight model for agentic coding and long-horizon tasks. This post shows how to deploy Beam on AWS: start with an Amazon SageMaker JumpStart real-time endpoint, or use Amazon SageMaker HyperPod Inference with JumpStart, SGLang, or vLLM for Kubernetes-native control over distributed GPU infrastructure.
