In the AI value chain, model training is the most resource-intensive and technically demanding stage, fundamentally determining a model’s performance ceiling. Training methods generally fall into four categories: centralized, distributed, federated, and decentralized training. Centralized training is controlled by a single entity with high efficiency but poses risks of monopoly and resource barriers. Distributed training involves multi-node collaboration but remains centrally orchestrated. Feder