Reflection's Beam Is the New Open-Weight Model Everyone Is Talking About

Reflection AI's new open-weight model, Beam, is a 501 billion parameter sparse mixture-of-experts (MoE) architecture. This design reduces inference compute by activating only 23 billion parameters per token. While this improves computational efficiency, the full model weights must still be loaded into memory, demanding significant hardware for deployment. Even quantized versions require multi-GPU server setups, shifting the primary cost from compute to memory.