Fluid compute exists for a new class of workloads. I/O bound backends like AI inference, agents, MCP servers, and anything that needs to scale instantly, but often remains idle between operations. These workloads do not follow traditional, quick request-response patterns. They’re long-running, unpredictable, and use cloud resources in new ways. Fluid quickly became the default compute model on Vercel, helping teams cut costs by up to 85% through optimizations like in-function concurrency. Today, we’re taking the efficiency and cost savings further with a new pricing model: you pay CPU rates only when your code is actively using CPU. Link to heading From servers to serverless In the early days of cloud computing, teams ran long-lived servers. You had to manage provisioning, handle scaling manually, and decide what happens during traffic spikes. Over-provisioning cloud resources was common, and idle time meant wasted money. Serverless changed that.…