Fujitsu and Scaleway bring CPU-based AI inference to Europe

MoU signed in November 2025 pairs Fujitsu's Arm-based MONAKA chip with Scaleway's cloud infrastructure.
In December 2025, Fujitsu and Scaleway announced a strategic collaboration to build a CPU-based AI inference option for European enterprises, Fujitsu Global reports. The MoU, signed November 27th, pairs Fujitsu's high-performance, energy-efficient Arm-based MONAKA CPU platform with Scaleway's European cloud infrastructure. The stated goals are data sovereignty, lower power consumption, and reduced supply chain risk.
This is a direct challenge to GPU-centric inference configurations. European enterprises face real pressure on both cost and compliance. A CPU-based inference path gives buyers a workload-matched alternative, with TCO as the selection lever rather than raw throughput. Scaleway is positioned as the distribution channel into that buyer base.
Seven months in, watch whether joint testing has produced workload benchmarks that hold up against GPU economics. The operating consequence is clear: inference is becoming a procurement decision, not just an engineering one. European cloud buyers now have a named CPU option to evaluate alongside existing GPU configurations.
Analysis
GPU is the default; CPU is the challenger. The question is whether MONAKA's TCO case survives contact with real enterprise workloads, or stays a compliance-driven niche.
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I just read this AI news story and want to understand it in my own context. Title: Fujitsu and Scaleway bring CPU-based AI inference to Europe Summary: Fujitsu and Scaleway signed an MoU on November 27, 2025 to test CPU-based AI inference across European cloud infrastructure. The FUJITSU-MONAKA Arm-based platform targets lower power consumption and data sovereignty for enterprise AI workloads. Category: Industry Source: Global, https://global.fujitsu/en-global/pr/news/2025/12/04-01 Using my own history and context, help me understand: 1. What is the core development and why does it matter? 2. Who are the major players involved and what are their motivations? 3. How does this fit into the broader AI landscape right now? 4. How does this apply to my own work, and what should I do or watch next? Be specific and plain spoken.
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