Open-Source Model Routing and Post-Training: Building Accurate, Fast, and Cost-Effective AI Systems
Routing and post-training open-source models significantly improve AI system accuracy, speed, and cost-efficiency. Harvey and Fireworks AI demonstrated that a hybrid architecture using GLM 5.1 as the primary worker with selective frontier model routing achieves superior quality and lower costs in legal tasks, proving this approach is a viable alternative to pure frontier models.
入选理由:Harvey实测显示混合法律Agent在质量和成本上均优于单一前沿模型。
