AWS vs Google Cloud: Pricing, Specs, Strengths & Weaknesses
Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for AWS and Google Cloud. Rates sourced from public APIs — verify current availability and billing terms before purchasing.
Overview
Strengths & Best For
AWS EC2 P5 instances are powered by NVIDIA H100 Tensor Core GPUs (up to 8× H100, 640 GB HBM3, 3,200 Gbps EFA networking). P5e and P5en instances use NVIDIA H200 GPUs (up to 8× H200, 1,128 GB HBM3e). P5en adds Gen5 PCIe and third-generation EFA for 35% lower latency. All three families deploy in EC2 UltraClusters scaling to 20,000 GPUs with petabit-scale nonblocking networking delivering 20 exaflops aggregate. SageMaker HyperPod manages resilient training clusters at any scale. Amazon Bedrock provides serverless access to DeepSeek v3.2, MiniMax, Kimi 3, Z.AI GLM 5, and Writer Palmyra. 30+ global regions with enterprise SLAs.
- P5/P5e/P5en: H100 and H200 in UltraClusters up to 20,000 GPUs
- 20 exaflops aggregate compute in EC2 UltraClusters
- 3,200 Gbps EFA networking with GPUDirect RDMA
- SageMaker HyperPod for resilient distributed training
- Amazon Bedrock: serverless access to DeepSeek, MiniMax, Kimi, GLM, Palmyra
- 30+ global regions with enterprise SLAs and compliance certifications
- Highest on-demand GPU rates among all providers
- Complex pricing — on-demand vs reserved vs spot vs savings plans
- GPU quota increases require support tickets and can take days
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Google Cloud's 2026 GPU lineup spans five accelerator-optimized machine series: A4X (NVIDIA GB200 Grace Blackwell Superchips, 720 GB HBM3e per 4-GPU node), A4 (NVIDIA B200, 1,440 GB HBM3e per 8-GPU node, 3,600 Gbps networking), A3 Ultra (NVIDIA H200, 1,128 GB HBM3e), A3 Mega/High/Edge (NVIDIA H100), and G4 (NVIDIA RTX PRO 6000 Blackwell, 96 GB GDDR7, GPU P2P communication). A2 series (A100 40/80 GB) and G2 (L4) remain available. AI Hypercomputer provides GKE and Slurm-integrated dense clusters. TPU v5 and v5e accelerators are available for TensorFlow/JAX workloads. Vertex AI provides managed ML pipelines. 30+ regions with sustained use and committed use discounts.
- A4X GB200 and A4 B200 — latest Blackwell hardware in cloud
- G4 RTX PRO 6000 with GPU P2P communication for inference
- AI Hypercomputer: GKE + Slurm-integrated dense clusters
- TPU v5/v5e for TensorFlow and JAX workloads
- Sustained use discounts and committed use contracts
- Vertex AI managed ML pipelines
- A4X and A4 require capacity reservation — not self-serve on-demand
- Premium pricing vs specialist GPU clouds
- Spot (preemptible) instances can be interrupted with little notice
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Key differences
AWS
P5 (H100), P5e/P5en (H200), UltraClusters up to 20,000 GPUs — hyperscale AI infrastructure
Google Cloud
A4X (GB200), A4 (B200), A3 Ultra (H200), G4 (RTX PRO 6000) — plus TPU v5 and AI Hypercomputer