Azure vs Google Cloud: Pricing, Specs, Strengths & Weaknesses
Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for Azure and Google Cloud. Rates sourced from public APIs — verify current availability and billing terms before purchasing.
Overview
Strengths & Best For
Microsoft Azure offers ND H100 v5 (8× H100, NVLink) and NC A100 v4 (4× A100) GPU VM series across 60+ regions, with enterprise compliance certifications including HIPAA, FedRAMP, and SOC 2 built in. Azure AI Foundry hosts Grok models from xAI alongside OpenAI, Anthropic, Meta, and Mistral models. Azure Machine Learning provides managed training and inference pipelines. Deep Active Directory, hybrid cloud, and Microsoft 365 integration makes Azure the natural GPU cloud for Microsoft-centric organizations. Savings plans (1yr/3yr) and reserved instances offer up to 53% off on-demand rates.
- 60+ regions — widest geographic coverage of any GPU cloud
- Enterprise compliance: HIPAA, FedRAMP, SOC 2, ISO 27001
- Azure AI Foundry: Grok, OpenAI, Anthropic, Meta, Mistral models
- Active Directory and hybrid cloud integration
- Savings plans up to 53% off on-demand rates
- Azure Machine Learning managed ML pipelines
- Most complex billing and quota system of any hyperscaler
- GPU quota increases require support tickets and can take days
- Higher on-demand rates vs specialist GPU clouds
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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
Azure
ND H100 v5, NC A100 v4, Grok on Azure AI Foundry — 60+ regions with enterprise compliance
Google Cloud
A4X (GB200), A4 (B200), A3 Ultra (H200), G4 (RTX PRO 6000) — plus TPU v5 and AI Hypercomputer