Reflection AI on Monday unveiled Beam, its first frontier open-weight model, sharpening the Western bid to answer the cheap, capable open models coming out of China. The two-year-old Brooklyn startup says Beam matches leading Chinese open models on advanced reasoning benchmarks at "a fraction of the token cost and inference time compute" of rivals.

Beam is a text-only mixture-of-experts model: 501 billion total parameters with 23 billion active, pretrained on 23.8 trillion tokens and a 1-million-token context window. Reflection says it was trained with high-compute reinforcement learning to excel at reasoning, coding and agentic tasks. By comparison, Z.ai's GLM-5.2 has roughly 744 billion total parameters with 40 billion active.

The performance claims have not been independently verified. On Reflection's own benchmarks, Beam scores on par with GLM-5.2 and beats today's leading Western open models while using three to four times less inference compute. The company also says Beam outscores Mira Murati's Thinking Machines Inkling on four coding tests where both report results — though Inkling is multimodal and Beam is text-only.

Reflection was founded in 2024 by two former Google DeepMind researchers and has raised about $4.7 billion from backers including Nvidia, Sequoia Capital and Lightspeed Venture Partners; its last round valued it at $25 billion pre-money. This summer it signed deals worth more than $7 billion with SpaceX and Nebius to lock in Nvidia GB300 chips through 2029.

The startup is pitching Beam and future models at enterprises and sovereign nations through "AI factories" — systems that let institutions train Reflection's models on their own proprietary data. It has begun testing a sovereign-AI partnership with South Korea's Shinsegae Group. Reflection says it will release Beam's weights and full technical details this month, with distribution through hyperscalers and neoclouds.

Sources