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Tensor Processing Units (TPUs)

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Google's Custom AI Hardware

While GPUs (like Nvidia H100s) are the industry standard, Google designs its own AI accelerators called TPUs (Tensor Processing Units).

TPUs are explicitly designed for the matrix multiplication operations required by neural networks. They offer massive cost-performance benefits, particularly for training large foundational models.

The latest 8th-generation TPUs (announced April 2026) are split into two specialized variants:

  • TPU 8t: Optimized for accelerated training workloads.
  • TPU 8i: Optimized for cost-effective, near-zero latency inference.

These are interconnected via the new Virgo Network fabric, designed for high-performance AI cluster scaling with Managed Lustre storage delivering up to 10 TB/s throughput.

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What makes Cloud TPUs different from standard GPUs?
They are optimized specifically for matrix multiplication operations inherent to neural networks
They are slower but cheaper
They only run on Windows
They are used for rendering 3D graphics
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