Reflection AI Introduces Beam Open Model to Challenge Chinese Dominance

Reflection AI has announced Beam, a massive open-weight AI model with 501 billion total parameters, set for full release later this month. The company, founded by former Google DeepMind researchers, positions Beam as a Western alternative to dominant Chinese open models, which have captured over 30% of the market. Beam uses a sparse Mixture-of-Experts architecture, with only 23 billion of its 501 billion parameters active at any given time, reducing computational costs.

The model was pre-trained on 23.8 trillion tokens and underwent reinforcement learning through 100 million practice rollouts on NVIDIA GB300 GPUs. Reflection claims Beam performs on par with Chinese rivals like Z.ai’s GLM-5.2 and Alibaba’s Qwen 3.8-Max, particularly in reasoning and coding tasks. Benchmarks show Beam scoring 80.9 on SWE-Bench Verified and 80.1 on Terminal Bench v2.1, while using 3 to 4 times less inference compute.

Reflection AI, valued at $25 billion with backers including Nvidia and Sequoia, aims to provide a robust open-weight alternative for Western users. The full model weights and technical documentation will be released under the Apache 2.0 license later in October 2026. The company’s partnerships with the Pentagon and the US Department of Energy highlight its focus on enterprise-scale AI solutions.

The efficiency claims of Beam could significantly impact enterprise AI adoption, though independent testing will be necessary to verify self-reported benchmarks. Coding performance, in particular, may vary once the model is widely tested.