Recently, drawing upon its proprietary MUSA software stack, Moore Threads has successfully achieved full-link inference support for the open-source biomolecular structure prediction model, Protenix-v2, on its integrated AI training and inference computing card, the MTT S5000. Actual test results reveal that the MTT S5000 demonstrates an average end-to-end inference performance that is approximately 26% superior to that of internationally recognized mainstream GPUs, while maintaining highly consistent accuracy in three-dimensional conformation prediction. It is noteworthy that Protenix-v2 was developed by ByteDance's Seed team and made publicly available in April 2026. This model surpasses the limitations of leading overseas models, which restrict access to their weights and prohibit private deployment. Protenix-v2 stands out as one of the few global open-source platforms capable of delivering high-precision end-to-end predictions for proteins, DNA, RNA, and small molecule ligand complexes.