Introducing Reflection Beam: an open-weight model for agentic coding on AWS

What happened

Reflection AI introduced Beam, an open-weight (a model whose trained parameters anyone may download) (published so anyone may download the trained model) model for agentic (AI that carries out multi-step tasks rather than answering one question) coding and long-horizon tasks such as maintaining code, using tools, interpreting results, and completing multi-step workflows. At launch, Beam is available in Amazon SageMaker (Python library) JumpStart in US East (N. Amazon Web Services is a cloud computing company based in Seattle.

Reflection AI's Beam is an open-weight model for agentic coding and long-horizon tasks. The open-weight release gives developers and researchers control over the runtime, deployment environment, and customization process.

Start with an Amazon SageMaker JumpStart real-time endpoint for a fully managed path. When you need Kubernetes (software that runs and manages applications across many servers)-native control over distributed GPU (a chip built for many calculations at once, used for graphics and AI) infrastructure, use Amazon SageMaker HyperPod Inference with JumpStart, SGLang, or vLLM.