Arm sees itself as central to this shift, arguing that AI workloads currently run largely in the cloud but will increasingly move to devices at the network edge.<\/p>\n
“When every interaction has to travel to a datacenter and back, there’s implications for latency, connectivity, the cost of delivering those services at enormous scale, so this is where we’re seeing it becoming more distributed, and I think few doubt now that basically everything you can push to the edge you will,” says Arm’s EVP of Edge AI, Chris Bergey.<\/p>\n
AI has evolved from background capabilities such as speech recognition and image processing into tools people actively engage with, including generative assistants, Bergey claims. Agentic AI goes further by interpreting objectives, coordinating applications and models, and executing sequences of actions.<\/p>\n
“So you have repeated inference, application logic, system orchestration, multiple workloads operating concurrently, and so that means you don’t just need more CPU performance. You need multiple high-performance CPUs working in parallel to keep all those different workloads running,” Bergey explains.<\/p>\n
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\n Arm C2-Ultra processor core information
\n Graphic: Arm\n <\/p>\n
With this in mind, the C2 CPU cluster features a new top-end C2-Ultra core that Arm claims delivers up to 15 percent higher single-thread performance than last year’s C1-Ultra.<\/p>\n
The C2-Ultra cores have a larger execution engine to keep more instructions in flight, and Arm claims more accurate branch prediction and better fetch and target prediction to keep the instruction pipelines fed.<\/p>\n
Arm’s chipmaker licensees can mix and match components to suit their requirements, as usual, but the firm touts a flagship cluster with two C2-Ultra cores, six efficiency-focused C2-Pro cores, and two SME2 units (Scalable Matrix Extensions<\/a>), compared with one SME2 unit in last year’s platform.<\/p>\n Doubling the SME2 capability enables up to a 70 percent speedup on the latest small language models, according to Arm, while the cluster topology supports private caches on the individual CPUs plus a large shared L3 cache. All of this is tied together by the DSU, or the DynamIQ Shared Unit.<\/p>\n Arm says the cluster has been optimized to reduce latency and keep concurrent agentic workloads responsive.<\/p>\n
![\"Arm's](\"https:\/\/www.europesays.com\/ie\/wp-content\/uploads\/2026\/09\/5294873.webp\")
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