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We ran 21,000 agentic simulations. A blend of open-source models matched the top performers.

We ran 21,000 agentic simulations. A blend of open-source models matched the top performers.

Most teams build around one model. Find the best, lock in, optimize around it. We tested the opposite: what happens when you route across multiple cost-efficient open-source models instead? On over 21,000 simulations of one of the hardest agentic benchmarks available, that blend scored 90.9%, within 7 points

By Louisa 13 Mar 2026
The Birth of a New Commodity Class and a Spot Market for Inference

The Birth of a New Commodity Class and a Spot Market for Inference

The gap between the #1 and #10 AI model shrank from 11.9% to 5.4% in a single year. Between #1 and #2? From 4.9% down to 0.7%. This data is reported by Stanford's AI Index, tracking Chatbot Arena scores. The most comprehensive public model

By Sishir Varghese 03 Mar 2026
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