With our original Max and Multimodal Max releases, we explored model routing across chat-based and multimodal tasks. This release continues our research into intelligent routing, tackling the challenge of balancing performance and cost across multi-turn, long-horizon tasks in Agent Arena.
Powered by 2.5+ million real-world Agent Arena sessions, Max routes users’ requests to the best models based on task complexity, cost and type of tasks. By accounting for each model’s strengths and performance-cost tradeoffs, Max achieves Pareto-frontier performance across task categories.
In the last 4 months, we’ve tested over 60 different agentic models on Arena, revealing distinct trade-offs between performance and cost, as well as the strengths and weaknesses of models across chat, code, and work tasks. Max matches each task with the model best suited to handle it, delivering a consistent, reliable experience across chat, work, and coding.
We recently deployed the agentic Max router in a live test, where it ranked #1 in Agent Arena with a score of +14.7% and a median cost of $3.27 per task over its testing period. Max outperformed the #1 public model at the time of testing, Fable 5.1 (Max), by 0.3% at 37.5% lower cost*. Below, we share further insights and a breakdown of Max’s routing distribution.
Max Router Breakdown
Max shifts the performance–cost Pareto frontier across code, chat, and work, with the largest gains in chat and work. The solid lines show the frontier with Max, compared with the dotted lines for public models alone. By routing between Fable 5.1, Astra medium and Astra max, Max delivers stronger results at a lower cost than directly selecting these models.
