Reflection's Beam becomes the most capable open-weight model built outside China
Reflection announced Beam, a 501-billion-parameter open-weight MoE that activates 23 billion parameters per token.
Reflection announced Beam, a text-only mixture-of-experts model with 501 billion total parameters and 23 billion active per token, built for coding, reasoning, and agentic work. The company says Beam matches GLM 5.2 on demanding reasoning while using three to four times less compute and approaches Qwen3.8-Max on coding benchmarks, though Kimi K3 still leads on raw performance. Reported scores include 80.9 on SWE-bench Verified and 80.1 on Terminal-Bench v2.1. A reinforcement-learning run used 10,500 Nvidia GB300 GPUs for over four weeks. Apache 2.0 weights are planned later this month; an early version is available to select users.