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NVIDIA B200 vs Google Cloud TPU v7 (Ironwood): Spec Comparison & Buyer's Guide

In AI infrastructure selection, NVIDIA B200 and Google Cloud TPU v7 (Ironwood) 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 B200Google Cloud TPU v7 (Ironwood)
VendorNVIDIAGoogle
ArchitectureBlackwell GB100TPU v7
ProcessTSMC 4NP—
Release Date2024 GTC，20252025
FP8 Compute9 PFLOPS—
FP16 Compute4.5 PFLOPS—
FP32 Compute——
INT8 Compute——
Memory Type——
Memory Capacity192 GB HBM3e—
Memory Bandwidth8 TB/s—
TDP Power1000 W600 W

Key Differences​

  • Power: Google Cloud TPU v7 (Ironwood) has a TDP of 600 W, lower than NVIDIA B200's 1000 W, friendlier to datacenter PUE and cooling.

Selection Advice​

  • When chasing extreme single-card compute and a mature toolchain, prioritize NVIDIA B200; if budget, power wall, or local support are hard constraints, Google Cloud TPU v7 (Ironwood) 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 B200 and Google Cloud TPU v7 (Ironwood)?​

The core difference is architecture and compute density: NVIDIA B200 uses Blackwell GB100, FP8 ~9 PFLOPS, memory 192 GB HBM3e; Google Cloud TPU v7 (Ironwood) uses TPU v7, FP8 ~No public FP8 data, memory —. See the comparison table above.

What is the TDP (power) of NVIDIA B200?​

NVIDIA B200 has a TDP of 1000 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 B200 and Google Cloud TPU v7 (Ironwood) differ in memory capacity?​

NVIDIA B200 is 192 GB HBM3e, Google Cloud TPU v7 (Ironwood) is —; the gap directly affects loadable model size and context length.