AWS Bedrock vs Google Vertex AI vs Azure OpenAI: Enterprise AI Platform Comparison
When companies move AI from experiments to production, they often want models running inside the cloud they already trust, with the same identity management, private networking, logging and compliance controls as the rest of their systems. Amazon Bedrock, Google Vertex AI and Azure OpenAI are the three major managed platforms for this. This guide compares what each offers and how to choose.
Short answer: start with the platform that matches your existing cloud. Bedrock for AWS shops wanting a choice of model providers, including Claude; Vertex AI for Google Cloud and Gemini-first teams; Azure OpenAI for Microsoft-centred organisations wanting OpenAI’s GPT models with Azure controls.
Side-by-side comparison
| Amazon Bedrock | Google Vertex AI | Azure OpenAI | |
|---|---|---|---|
| Cloud | AWS | Google Cloud | Microsoft Azure |
| Headline models | Multiple providers, including Anthropic Claude, Amazon’s own models, Meta Llama and Mistral | Google Gemini, plus third-party and open models including Claude and Llama | OpenAI GPT models; Microsoft’s wider AI platform also offers other providers |
| Best for | Model choice inside AWS | Gemini, long context, Google data stack | Microsoft 365 and Azure organisations |
| Ecosystem | AWS services, Lambda, S3, IAM | BigQuery, Google Workspace, IAM | Microsoft 365, Entra ID, Azure services |
| Enterprise controls | IAM, private networking, logging | IAM, private networking, logging | Entra ID, private networking, logging |
Model line-ups change frequently on all three platforms; check each platform’s current model catalogue and regional availability. For a comparison of the model families themselves, see Gemini vs GPT vs Claude vs Qwen.
Amazon Bedrock
Bedrock gives AWS customers access to models from several providers through one service, which makes it easy to compare and switch models. It is a common way to use Anthropic’s Claude inside AWS, with requests staying within your AWS account’s security boundary. It also offers tools for retrieval from your own data, guardrails and agents.
Google Vertex AI
Vertex AI is Google Cloud’s AI platform, centred on the Gemini models and their long context and multimodal strengths, with a model garden of third-party and open models. It suits organisations already using BigQuery and Google Workspace, and teams that want Gemini at enterprise scale.
Azure OpenAI
Azure OpenAI provides OpenAI’s GPT models within Microsoft Azure, with Azure’s identity, networking and compliance tooling. It is the natural fit for organisations standardised on Microsoft 365 and Azure, and for teams building on Microsoft’s Copilot ecosystem.
How to choose
- Start with your cloud: identity, networking, billing and compliance are already in place there
- Confirm model fit: make sure the platform offers the models you need, in your region
- Check data and compliance terms: review data handling, retention and certifications; see SOC 2 vs ISO 27001
- Compare total cost: token prices, provisioned capacity options and data transfer
- Keep switching easy: wrap model calls behind your own interface so you can change models later
When to skip the cloud platforms
Startups and smaller businesses often move faster calling provider APIs directly, especially from no-code apps. Bubble.io apps, for example, connect to OpenAI, Anthropic or Google through the API Connector; see OpenAI and Claude in Bubble.io and AI API integration. Move to a cloud AI platform when security, scale or existing cloud commitments call for it.
Frequently asked questions
What is the difference between AWS Bedrock, Vertex AI and Azure OpenAI?
Each is a cloud provider's managed service for using AI models inside its cloud. Amazon Bedrock offers models from several providers, including Anthropic's Claude; Google Vertex AI centres on Google's Gemini and also offers third-party and open models; Azure OpenAI provides OpenAI's GPT models within Microsoft's cloud.
Which enterprise AI platform should I choose?
Usually the one that matches the cloud you already use, because identity, networking, billing and compliance are already set up there. Then confirm the platform offers the models you need for your tasks.
Can I use Claude on AWS or Google Cloud?
Yes. Anthropic's Claude models are available through Amazon Bedrock and through Google Vertex AI, as well as directly from Anthropic's own API.
Is my data used to train models on these platforms?
Each platform documents how it handles prompts and outputs, and their enterprise terms generally restrict use of customer data. Read the current data-handling terms for the specific service and region before sending sensitive data.
Should a small business use these platforms or call AI APIs directly?
Small businesses and startups often find direct provider APIs simpler and cheaper to start with. Cloud AI platforms make most sense when you already run on that cloud or need its enterprise security, private networking and compliance controls.
Choosing an AI platform for production?
Book a free Idea Audit. We will recommend the simplest secure setup for your models, data and budget.