Crusoe Video: Yutori Chief Scientist Dhruv Batra on Agent Inference Costs and Scaling
Crusoe released a video case study featuring Yutori. Co-founder and Chief Scientist Dhruv Batra details how his 14-person team utilizes Crusoe's infrastructure for training and inference, claiming a roughly 10x scale-up on the same footprint and comparing task costs on the OSWorld 2.0 benchmark.
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Crusoe published a video case study on September 24, 2026, featuring Yutori. In the video, Yutori Co-founder and Chief Scientist Dhruv Batra explains how his 14-person team works with Crusoe from training through inference.
According to the video description, Yutori's Navigator n2 model was trained in part on Crusoe Cloud. The model reads screens like a person and clicks, scrolls, and types accordingly, allowing it to work on websites and apps that lack APIs.
Batra notes that Yutori uses Crusoe Managed Inference with a Tailored Deployment and a cluster-wide KV cache for its cache-heavy, multistep workload. The video claims this architecture enabled a roughly 10x scale-up on the same growing footprint, serving every Navigator generation from n1 to n2.
Additionally, the video cites OSWorld 2.0 benchmark data, stating a cost of approximately $1.46 per task for Yutori, compared to about $13 to $40+ per task for frontier models. These figures and performance claims originate from joint marketing materials by the vendor and customer and have not been independently verified.