Introducing Active CPU pricing for Fluid compute

Fluid compute, a new model for handling I/O bound workloads like AI inference and MCP servers, has emerged as an efficient solution for modern application needs, particularly on the Vercel platform. It deviates from traditional serverless models by orchestrating multiple concurrent requests on shared resources, eliminating cold starts and reusing idle time, leading to substantial cost savings and improved efficiency. This approach has become the default for AI workloads on Vercel, resulting in cost reductions of up to 90% due to intelligent resource sharing. To further enhance cost-efficiency, Vercel has introduced an Active CPU pricing model, which charges for CPU usage only when code is actively executing, aligning costs with actual compute work rather than wall time. This model, alongside usage-based billing for provisioned memory and invocations, significantly reduces costs, particularly for workloads with high idle time. The Fluid platform is designed to support modern applications with standard runtimes like Node.js and Python, optimizing infrastructure while maintaining flexibility and performance. The Active CPU pricing model is now available by default for most Vercel users, promising to further optimize costs and resource usage for AI-powered applications.