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NewsMaterial3 min readDisconfirmAI Editorial

Intel Explains AI Deployment Cost Strategy: Agentic AI Increases CPU Demand

At a briefing on its next-generation processor architecture, Intel explained how to position compute power, power consumption, and costs across different workloads—moving from the cost-cutting approach of the Core 3 Series and the high-memory inference focus of the GPU D series to the orchestration expansion of Diamond Rapids. The company also argued that agentic AI will drive increased demand for CPUs.

2026-11-10 16:41 GMT+8

Semiconductor competition is not just about whose chips are faster, but also about who can best configure cost, power consumption, and computing capability in the right places. At a next-generation processor architecture briefing held on November 10, Intel discussed everything from the Core 3 Series to the data center GPU D series and the next-generation Xeon Diamond Rapids. Underlying these discussions is a common question: as AI gradually enters daily work, how much compute power do users actually need, and how much are they willing to pay?

The strategy for the Core 3 Series (codenamed Wildcat Lake) is one of subtraction. It utilizes Intel's 18A process technology, with a maximum configuration of two performance cores and four low-power efficiency cores, paired with the Xe3 graphics architecture and a neural processing unit, bringing next-generation cores into mainstream price points. However, the costs of new process technologies do not disappear into thin air. Yu Xiaolun, Product Manager for Intel's Client Computing and Physical AI Group, stated that mainstream-priced products do not necessarily have to rely on previous-generation processes. To address this, Intel has adopted single-channel memory, streamlined input/output configurations, and uses organic substrate multi-chip packaging via UCIe chiplet interconnects to reduce packaging and system costs. These adjustments reduce the compute die area by approximately 38% and allow motherboards to be reduced from eight layers to six. This means that price competition for mainstream products must consider memory, circuit boards, and components together, rather than looking solely at the processor's selling price.

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Regarding agentic AI, Zheng Zhicheng, Director of Commercial Business for Intel's Business and Marketing Group, presented an argument: the fact that CPUs are more important does not mean GPUs are unimportant. His logic is that agentic AI requires not only model inference but also general-purpose computing environments to execute tools, manage data, and coordinate tasks; therefore, CPU demand will also increase. This provides a new perspective for understanding server requirements, but the article notes that the usage volume of agent services cannot be directly converted into equivalent physical core procurement. Actual demand is still influenced by the number of simultaneous users, resource scheduling, and task execution time.

The GPU D series (codenamed Crescent Island) bets on memory capacity and deployment costs. It adopts the Xe3P architecture, focusing on inference applications, with announced specifications including 350 watts of power consumption, 1.5 TB per second of memory bandwidth, and 1.3 PFLOPS of FP8 computing performance. Intel-branded cards are configured with 160 GB of LPDDR5X, while partner designs can reach up to 480 GB. Large memory serves not only to hold model weights but also key-value caches required for long contexts and working data for multiple simultaneous users. Paired with standard PCIe and air-cooling designs, Intel hopes to lower the threshold for adoption in existing server rooms. In a Q&A session, Zheng Zhicheng clarified that 160 GB is not the capacity floor for the entire series; smaller capacity versions may exist, but the 128 GB and 96 GB examples shown on-site cannot yet be considered official specifications.

The next-generation Xeon processor, Diamond Rapids, utilizes Intel's 18A-P process technology, offering up to 256 cores, 1.28 GB of last-level cache, 16 memory channels, and 128 lanes supporting PCIe Gen 6 and CXL 3.0, along with Foveros Direct 3D and UCIe-S interconnects. Intel claims that compared to 18A, 18A-P improves performance by approximately 9% at the same power consumption, or reduces power consumption by approximately 18% at the same performance level. However, this is a comparison at the process node level and cannot be directly equated to improvements in an entire server.

Whether these specifications can translate into stable supply, mature software, and prices that customers are willing to adopt remains the next test. For enterprises, the actual basis for evaluating hardware is how much time, electricity, and cost are required to complete each task.

Sources

  • inside.com.twINSIDE↗
  • sec.gov↗
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