RELEASE · MODELS · #2126
Reflection releases Beam 1.0 — a 501B-parameter open-weight agentic coding model available on AWS
Reflection AI released Beam 1.0, an open-weight sparse mixture-of-experts model (501 billion total parameters, 23 billion active parameters, 1M token effective context) for agentic coding and long-horizon workflows. Beam 1.0 weights are published on Hugging Face under an Apache 2.0 license and the model is available via Amazon SageMaker JumpStart in US East (N. Virginia and Ohio) with deployment options including JumpStart real-time endpoints, SageMaker HyperPod Inference, and self-managed runtimes via SGLang or vLLM; checkpoints are offered in BF16, FP8, and NVFP4 formats.
KEY POINTS
- Reflection AI released Beam 1.0, an open-weight sparse mixture-of-experts model (501 billion total parameters, 23 billion active parameters, 1M token effective context) for agentic coding and long-horizon workflows.
- Beam 1.0 weights are published on Hugging Face under an Apache 2.0 license and the model is available via Amazon SageMaker JumpStart in US East (N.
- Virginia and Ohio) with deployment options including JumpStart real-time endpoints, SageMaker HyperPod Inference, and self-managed runtimes via SGLang or vLLM; checkpoints are offered in BF16, FP8, and NVFP4 formats.
WHY IT MATTERS
An open-weight, large sparse MoE model optimized for agentic coding and released under Apache 2.0 — plus direct availability on AWS managed and self-managed serving paths — materially lowers barriers for researchers and developers building and deploying agentic coding systems.