Premium inference is designed to solve the real problem that agents run into at scale. Agentic systems do not answer one prompt and stop. They reason, call tools, query databases, compile code, invoke sandboxes, validate results, and return to inference again and again until the work is done.
That is why the bar for premium inference has to be so high: decoding at roughly 200+ tokens per second on trillion-parameter-class models while staying efficient enough to fit real deployments. Fast decode, support for the largest models, practical chip footprint, and energy-efficient deployment are the core requirements.
Meeting that bar takes more than one processor. It takes a blueprint. GPUs handle compute-bound prefill. RDUs handle fast decode. CPUs play two roles around the model: as the host CPU, they prepare data and orchestrate execution between GPUs and RDUs; as the action CPU, they run the agent frameworks, compilers, sandboxes, vector databases, APIs, and enterprise systems that make agents useful in production.
That is the blueprint behind SambaNova’s announcement with Intel. Together, the two companies are bringing a heterogeneous inference design to enterprises, cloud providers, and sovereign AI programs that need premium inference for real agentic workloads.
