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NVIDIA H100 SXM vs Google Cloud TPU v5p: Spec Comparison & Buyer's Guide

In AI infrastructure selection, NVIDIA H100 SXM and Google Cloud TPU v5p are two accelerators frequently compared. This article contrasts them item by item — architecture, compute, memory, power, and release cadence — to help you quickly judge which fits training or inference workloads.

Spec Comparison Table

VendorNVIDIA H100 SXMGoogle Cloud TPU v5p
VendorNVIDIAGoogle
ArchitectureHopper GH100Google TPU v5p
ProcessTSMC 4NTSMC 5nm
Release Date2022 3 GTC2023-12-05
FP8 Compute3,958 TFLOPS
FP16 Compute
FP32 Compute67 TFLOPS
INT8 Compute
Memory Type
Memory Capacity80 GB HBM3
Memory Bandwidth3.35 TB/s
TDP Power700 W300 W

Key Differences

  • Power: Google Cloud TPU v5p has a TDP of 300 W, lower than NVIDIA H100 SXM's 700 W, friendlier to datacenter PUE and cooling.

Selection Advice

  • When chasing extreme single-card compute and a mature toolchain, prioritize NVIDIA H100 SXM; if budget, power wall, or local support are hard constraints, Google Cloud TPU v5p often fits better. Use this site's AI Compute Card Comparison Tool to validate multiple chips side-by-side before deciding.

FAQ

What are the main differences between NVIDIA H100 SXM and Google Cloud TPU v5p?

The core difference is architecture and compute density: NVIDIA H100 SXM uses Hopper GH100, FP8 ~3,958 TFLOPS, memory 80 GB HBM3; Google Cloud TPU v5p uses Google TPU v5p, FP8 ~No public FP8 data, memory —. See the comparison table above.

What is the TDP (power) of NVIDIA H100 SXM?

NVIDIA H100 SXM has a TDP of 700 W; actual whole-system power also includes board, fans, and PUE.

Which is better for large-model training / inference?

Training values memory capacity, bandwidth, and multi-card interconnect; inference values single-card throughput and power efficiency. Combine the "Key Differences" and "Selection Advice" above with your batch size, model size, and SLA.

How much do NVIDIA H100 SXM and Google Cloud TPU v5p differ in memory capacity?

NVIDIA H100 SXM is 80 GB HBM3, Google Cloud TPU v5p is —; the gap directly affects loadable model size and context length.