Next up is the N4A instance that is also aimed at general workloads such as data processing, web services, and development environments, but it scales up to 64 vCPUs, 512 GB of DDR5 RAM, and 50 Gbps networking, making it a more affordable offering.
The other preview model is C4A Metal, which is a bare-metal configuration that presumably exposes the full Axion hardware stack directly to customers: up to 96 vCPUs, 768 GB of DDR5 memory, and 100 Gbps networking. The instance is ment for specialized or license-restricted applications or Arm-native development.
These new launches built upon a decade of Google's custom silicon development which began with the original TPU and continued through YouTube's VCUs , Tensor mobile processors, and Titanium infrastructure. The Axion CPU — Google's first Arm-based general-purpose server processor — completes the portfolio of the company's custom chips, and the Ironwood TPU set the stage for competition against the best AI accelerators on the market.
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Anton Shilov Social Links Navigation Contributing Writer Anton Shilov is a contributing writer at Tom’s Hardware. Over the past couple of decades, he has covered everything from CPUs and GPUs to supercomputers and from modern process technologies and latest fab tools to high-tech industry trends.
bit_user According to this, Google's Axion CPUs are made on TSMC N3: https://www.trendforce.com/news/2025/10/21/news-googles-axion-cpu-reportedly-built-on-tsmcs-3nm-set-to-drive-foundrys-data-center-revenue-growth/ The article said: It provides up to 72 vCPUs, 576 GB of DDR5 memory Probably 96 GiB/channel @ 6-channel (384-bit). It works out to 8 GiB/core, which is probably enough for most general-purpose server workloads. Reply
jp7189 I don't see any data about power usage which is just as important as performance numbers these days. Reply
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Reference reading
- https://www.tomshardware.com/tech-industry/artificial-intelligence/SPONSORED_LINK_URL
- https://www.tomshardware.com/tech-industry/artificial-intelligence/google-deploys-new-axion-cpus-and-seventh-gen-ironwood-tpu-training-and-inferencing-pods-beat-nvidia-gb300-and-shape-ai-hypercomputer-model#main
- https://www.tomshardware.com
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