Agents
Why CPUs Are the Workhorse of Agentic AI Infrastructure
While GPUs remain essential for LLM training and inference, enterprise‑scale agentic AI workloads shift the focus to orchestration rather than raw compute. Agents must break down requests into subtask
While GPUs remain essential for LLM training and inference, enterprise‑scale agentic AI workloads shift the focus to orchestration rather than raw compute. Agents must break down requests into subtasks, delegate them, query databases, make API calls, check permissions, retrieve memory, validate outputs, and loop back—all of which rely on CPU‑based control logic, state management, and integration with external services. Consequently, a sustainable agentic AI infrastructure couples GPUs for heavy numeric work with CPUs as the core orchestrators to deliver responsive, enterprise‑level user experiences.
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Source: Vultr | 2026-09-09