Hyperscaler

Google Cloud

The only place to rent TPUs, plus a full NVIDIA lineup on A3/A4 instances.

GCP's differentiator is TPU pods, v5e for cost, v6e (Trillium) for performance, with pricing per chip-hour that undercuts equivalent NVIDIA FLOPS when your stack speaks JAX/XLA. NVIDIA capacity (H100 A3, B200 A4) is competitive with other hyperscalers. DWS (Dynamic Workload Scheduler) eases short-term capacity.

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GPU pricing on GCP

On-demand list per GPU-hour, last reviewed 2026-09. Methodology.

GPU $/GPU-hr vs cheapest Notes
T4 $0.35 cheapest n1 + T4
L4 $0.71 2.0× g2-standard-4
TPU v5e $1.20 3.4× per chip-hour, us-west4
TPU v6e $2.70 7.7× per chip-hour, us-east5
A100 40GB $2.93 8.4× a2-highgpu ÷ 8
A100 80GB $3.93 11.2× a2-ultragpu ÷ 8
H100 SXM $5.90 16.9× A3 ÷ 8
B200 $8.20 23.4× A4 ÷ 8

Strengths

  • TPUs, exclusive
  • Strong Kubernetes (GKE) GPU story
  • Committed-use discounts apply to GPUs

Watch for

  • TPU lock-in is real (XLA)
  • Regional GPU availability varies widely

Alternatives

AWS

The biggest cloud. The deepest catalog, the highest list prices, the most enterprise glue.

Azure

OpenAI's landlord. Big H100/H200 and MI300X fleets with enterprise Microsoft integration.

OCI

The hyperscaler that prices like a neocloud. Bare-metal GPU shapes with no virtualization tax.