GoKawiilReflection releases open-weight 501B parameter model Beam for coding and reasoning
Reflection has unveiled Beam, its first open-weight model with 501 billion parameters, designed for tasks like coding, reasoning, and agentic workloads. The model was pretrained on 23.8 trillion tokens and refined through extensive reinforcement learning using over 100 million rollouts on NVIDIA GPUs, aiming to achieve high efficiency and performance. Beam is currently undergoing final testing before a public release of its weights and technical documentation later this month.
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The release of Beam marks a significant step in the open-weight AI model landscape, offering a large-scale model that balances performance with inference efficiency. Its focus on coding and agentic tasks could influence future developments in open AI models, potentially enabling broader access and innovation in AI applications. This development also highlights ongoing investments in large-scale training and reinforcement learning to push the capabilities of open models.
- Beam is a 501B parameter open-weight model focused on coding and reasoning.
- It was pretrained on 23.8 trillion tokens and refined through extensive reinforcement learning.
- The model aims to offer competitive performance with improved inference efficiency.
Source: reflection.ai, 2026-10-05
Published there as: “Beam: Reflection's 501B open-weight model”
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