Benchmarking over 1,000 agentic tasks demonstrates that routing between the open-source Kimi K3 model and the closed Fable 5 model creates a new state-of-the-art (SoTA) approach that surpasses the performance of either model alone. While both models perform competitively in general benchmarks, they possess distinct specializations—K3 excels in terminal, symbolic math, and dev tooling, whereas Fable leads in web, data visualization, and multi-language breadth. By architecting a router to leverage these specific strengths, teams can achieve a 93% task accuracy rate and up to 50x better cost-efficiency compared to using Fable in isolation, effectively proving that relying on a single model is no longer optimal.
GLM 5.2 is half of K3’s cost on AI analysis, is faster tps, and less token burn. V4 flash is also above 50 (loosely getting more than half questions perfect) in AI index score and even much cheaper. This approach has much better cost curve potential, even if k3/fable are included in possible routing.