Comparison guide
AWS Bedrock vs Google Vertex AI vs Azure OpenAI (2026)
The definitive comparison for engineering and product teams choosing a managed AI platform. Models, pricing, orchestration, compliance, and our recommendation.
Quick answer
AWS Bedrock leads on multi-model choice; Google Vertex AI on long-context and BigQuery; Azure OpenAI on Microsoft-native enterprise compliance.
Last updated: May 2026
| Feature | AWS Bedrock | Google Vertex AI | Azure OpenAI |
|---|---|---|---|
| Model variety | Best (Claude, GPT, Llama, Mistral, Titan) | Good (Gemini, Llama, others) | GPT family + some Llama |
| Long context (1M+ tokens) | |||
| Managed agents | Bedrock Agents (mature) | Agent Builder (strong) | AI Foundry (solid) |
| RAG / Knowledge bases | Bedrock Knowledge Bases | Vertex AI Search | Azure AI Search |
| Enterprise compliance | Excellent | Good | Best (M365 ecosystem) |
| Multi-modal (image/audio/video) | |||
| Best for data in… | S3, DynamoDB, Redshift | BigQuery, GCS, Spanner | Azure Blob, Cosmos, SQL |
| Pricing model | Per token + managed infra | Per token + per query | Per token (PAYG or PTU) |
| On-prem / VPC isolation | VPC + PrivateLink | VPC Service Controls | Private Endpoints + vNet |
| Partner ecosystems | Largest overall | Strong in data/ML | Dominant in enterprise IT |
Our recommendation
Choose AWS Bedrock if you want multi-model flexibility and are already on AWS. Choose Vertex AI for long-context or BigQuery-heavy workloads. Choose Azure OpenAI for Microsoft-native enterprises with M365/SharePoint data or compliance requirements.
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