About 18; min
Enterprise AI deployment typically runs through one of three major cloud providers. AWS Bedrock, Azure OpenAI Service, and Google Vertex AI each offer managed access to frontier AI models with enterprise security, compliance, and integration into their respective cloud platforms. The choice often depends on which cloud you already use — but the model selection, pricing, and capabilities differ enough to warrant comparison.
Quick Comparison
| Feature | AWS Bedrock | Azure OpenAI | Google Vertex AI |
|---|---|---|---|
| Cloud Provider | Amazon Web Services | Microsoft Azure | Google Cloud |
| Flagship Models | Claude, Llama, Mistral, Titan | GPT-4o, o1, DALL-E | Gemini, Claude, Llama |
| Multi-Model | Yes (20+ models) | OpenAI models only | Yes (Gemini + partners) |
| Fine-Tuning | Yes (select models) | Yes (GPT-4o, GPT-3.5) | Yes (Gemini, open models) |
| RAG Support | Knowledge Bases | Azure AI Search | Vertex AI Search |
| Agents | Bedrock Agents | Azure AI Agent Service | Vertex AI Agents |
| Guardrails | Bedrock Guardrails | Content filtering | Safety filters |
| Data Residency | Regional | Regional | Regional |
| Compliance | HIPAA, SOC, FedRAMP | HIPAA, SOC, FedRAMP | HIPAA, SOC, FedRAMP |
AWS Bedrock Overview
AWS Bedrock provides a single API to access models from Anthropic (Claude), Meta (Llama), Mistral, Cohere, Stability AI, and Amazon’s own Titan models. Claude Sonnet on Bedrock costs $3.00/M input and $15.00/M output tokens — the same as Anthropic’s direct API. Llama 3.1 70B runs at $2.65/M input and $3.50/M output. Bedrock Knowledge Bases build RAG pipelines that connect models to your documents in S3. Bedrock Agents create multi-step AI workflows that call APIs, query databases, and process business logic. Bedrock Guardrails filter harmful content and enforce topic restrictions. The key advantage: model choice. Switch between Claude, Llama, and Mistral without changing your infrastructure. For AWS-native organizations, Bedrock integrates with IAM, CloudWatch, VPC, and every AWS service.
Azure OpenAI Service Overview
Azure OpenAI provides exclusive managed access to OpenAI’s models — GPT-4o, GPT-4 Turbo, o1, DALL-E, Whisper, and text-embedding models. GPT-4o costs $2.50/M input and $10.00/M output tokens. The o1 reasoning model costs $15.00/M input and $60.00/M output. Azure handles deployment, scaling, and compliance within your Azure subscription. Each model deployment gets a dedicated endpoint with configurable rate limits. Azure AI Search provides vector and hybrid search for RAG applications. The integration with Microsoft 365 Copilot, Power Platform, and Dynamics 365 extends AI across the Microsoft stack. For organizations committed to OpenAI’s models and running on Azure, this service provides the most direct and compliant access.
Google Vertex AI Overview
Vertex AI hosts Google’s Gemini models alongside partner models including Claude and Llama through the Model Garden. Gemini 1.5 Pro costs $1.25/M input and $5.00/M output tokens (standard), or $2.50/$10.00 for the 2M context variant. Gemini 2.0 Flash at $0.10/M input is among the cheapest frontier-class APIs. Vertex AI Search and Conversation builds RAG applications connected to Google Cloud Storage, BigQuery, and third-party sources. Grounding with Google Search adds real-time web information to model responses. The Model Garden provides 150+ models for evaluation and deployment. For organizations on Google Cloud, Vertex AI offers the broadest model access with competitive Gemini pricing.
Model Availability
| Model | AWS Bedrock | Azure OpenAI | Google Vertex AI |
|---|---|---|---|
| GPT-4o / o1 | No | Yes (exclusive) | No |
| Claude (Anthropic) | Yes | No | Yes |
| Gemini | No | No | Yes (native) |
| Llama 3.1 | Yes | No | Yes |
| Mistral | Yes | No | Yes |
| DALL-E | No | Yes | No |
| Imagen | No | No | Yes |
| Stability AI | Yes | No | No |
| Cohere | Yes | No | No |
Pricing Comparison (Key Models)
| Model | Platform | Input/M tokens | Output/M tokens |
|---|---|---|---|
| Claude Sonnet 4 | AWS Bedrock | $3.00 | $15.00 |
| Claude Sonnet 4 | Vertex AI | $3.00 | $15.00 |
| GPT-4o | Azure OpenAI | $2.50 | $10.00 |
| Gemini 1.5 Pro | Vertex AI | $1.25 | $5.00 |
| Gemini 2.0 Flash | Vertex AI | $0.10 | $0.40 |
| Llama 3.1 70B | AWS Bedrock | $2.65 | $3.50 |
Enterprise Features
All three platforms meet enterprise compliance requirements — HIPAA, SOC 2, ISO 27001, and FedRAMP certification. Data stays within your chosen region and is not used for model training. VPC/VNet integration keeps AI traffic on private networks. IAM/RBAC controls who can access which models and endpoints.
Where they differ: AWS Bedrock’s Guardrails provide the most configurable content filtering — define denied topics, sensitive information filters, and grounding checks that apply across any model. Azure OpenAI includes content filtering by default with configurable severity levels. Vertex AI’s safety filters are applied at the model level with adjustable thresholds. For organizations with specific content policy requirements, Bedrock’s model-agnostic guardrails are the most flexible.
Who Should Pick What
Pick AWS Bedrock if:
- You want access to Claude, Llama, and Mistral through a single managed API
- Model flexibility matters — switch providers without changing infrastructure
- Your organization runs on AWS and needs native IAM, VPC, and CloudWatch integration
- Bedrock Agents and Knowledge Bases cover your RAG and automation needs
Pick Azure OpenAI if:
- GPT-4o and o1 are the models your team has built around
- Microsoft 365 Copilot and Power Platform integration extends AI across your org
- Your infrastructure is on Azure and compliance requires keeping AI within Azure
- DALL-E and Whisper are part of your multimodal requirements
Pick Google Vertex AI if:
- Gemini’s pricing ($0.10/M for Flash) fits your high-volume budget
- The 2M token context window enables use cases other platforms can’t handle
- Google Cloud is your primary infrastructure with BigQuery and GCS integration
- Model Garden’s 150+ models let you evaluate and compare before committing
AWS Bedrock wins for the widest model selection through a single managed API. The ability to run Claude, Llama, Mistral, and Cohere without switching platforms gives teams flexibility that Azure (OpenAI only) and Vertex (Gemini-focused) can’t match. Bedrock Guardrails add enterprise content controls that work across any model. Google Vertex AI earns runner-up for the most aggressive pricing — Gemini 2.0 Flash at $0.10/M tokens and the 2M context window create unique capabilities at low cost. Azure OpenAI is essential for teams committed to GPT-4o and the Microsoft stack but limits you to a single model provider.
FAQ
Is pricing the same as using the model providers directly?
Generally yes, though small differences exist. Claude on Bedrock costs the same as Anthropic’s direct API. Azure OpenAI pricing matches OpenAI’s API rates. The cloud platforms add enterprise features (compliance, VPC, guardrails) at the same per-token price.
Can I use multiple cloud AI platforms?
Yes. Multi-cloud AI strategies are common — using Azure OpenAI for GPT-4o, Bedrock for Claude, and Vertex for Gemini Flash. An abstraction layer like LiteLLM routes requests to the cheapest or best-performing model per task.
Which is best for RAG applications?
All three offer managed RAG. AWS Knowledge Bases integrate with S3 and OpenSearch. Azure AI Search provides hybrid vector search. Vertex AI Search connects to BigQuery and GCS. Choose based on where your documents and data already live.
Do I need approval to use Azure OpenAI?
Azure OpenAI previously required application approval. As of 2025, access is generally available for most models, though some (GPT-4 Turbo, o1) may still require approval in certain regions. AWS Bedrock and Vertex AI are available without approval gates.
