Qualcomm Cloud AI 100 Ultra — 64-Core Data Center AI Inference Accelerator

Specifications

Overview

The Qualcomm Cloud AI 100 Ultra is the four-SoC member of the Cloud AI 100 accelerator line: 16 AI cores per SoC, 64 cores per card, built on a 7 nm process and carrying 144 MB of on-card AI SRAM. It is designed for inference specifically — not training — and competes on performance per watt and per dollar in large-scale LLM serving.

Qualcomm positions the Ultra tier for the heaviest inference workloads in a deployment, with the Pro and Standard SKUs slotting underneath for lower-density nodes. Because all three share the same Cloud AI SDK and compiler, a model compiled once can be deployed across the tier.

QS Compute supplies Cloud AI 100 accelerator cards alongside the NVIDIA and AMD inference parts and the Tenstorrent Wormhole/Blackhole cards, so customers can benchmark inference cost per token across architectures before standardising.

Key Benefits

64 AI cores across four SoCs give the highest inference throughput in the Cloud AI 100 family. 144 MB AI SRAM keeps weights and activations close to compute. Single SDK across the tier lets one compiled model deploy on Ultra, Pro or Standard cards. 7 nm / inference-first design lowers power per token versus general-purpose GPUs.

Applications

Large-scale LLM and generative-AI inference serving; recommendation and embedding inference at the edge; computer vision and video analytics pipelines; and cost-sensitive inference nodes where tokens-per-watt matters more than training capability.

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