Microsoft Foundry vs Google Vertex AI: pricing, features and which to choose

Microsoft Foundry is the successor to Azure AI Studio and Azure AI Foundry, and Microsoft calls it its AI app and agent factory. It serves developers and enterprises building on Azure, especially companies that already use Microsoft 365, Entra ID, Fabric and Azure security tools. The portal at ai.azure.com, SDKs and a Visual Studio Code extension cover the full cycle: choose a model, ground it in company data, build an agent, evaluate it and monitor it in production. Because it runs inside Azure subscriptions, usage counts toward existing Azure commitments, and Microsoft's regional and data zone deployments help with data residency requirements in the US, Europe and Asia Pacific.

Foundry Models gives access to more than 11,000 models, according to Microsoft's pricing page. That includes OpenAI models, which Microsoft hosts on Azure, such as the GPT-6 family that reached general availability in September 2026, plus Microsoft's own MAI models, Meta's Llama, Mistral, DeepSeek, xAI's Grok and many open models from Hugging Face. Since November 2025 Anthropic's Claude models have also been available in Foundry, which Microsoft says made Azure the only cloud offering both Claude and GPT frontier models. Teams can benchmark models side by side, use a model router that picks a model per request and fine-tune or distill models through Azure Machine Learning.

Microsoft Foundry's strengths are the largest model catalog among the big clouds, first-party hosting of OpenAI models, Claude and GPT on one platform, deep Microsoft 365 and Entra integration, and agent tooling with MCP and governance built in. Its weaknesses are Azure complexity, frequent renaming that confuses documentation, pricing that changes by region and deployment type, and quotas that can limit access to new models. Amazon Bedrock is the AWS counterpart. Google Vertex AI leads with Gemini on Google Cloud. Microsoft Copilot Studio offers low-code agents for business users. Hugging Face hosts open models. Choose Foundry if your organization runs on Azure and Microsoft 365.

Google launched Vertex AI in May 2021 to unify its machine learning services for training, deploying and monitoring models. With the rise of generative AI it became Google Cloud's main platform for enterprises using Gemini and other foundation models, and in 2026 Google began presenting it as the Gemini Enterprise Agent Platform, which its documentation describes as an evolution of Vertex AI. It serves data scientists, machine learning engineers and application developers at companies that run on Google Cloud, who need enterprise security, data residency, governance and integration with BigQuery and other Google data services rather than a consumer API key.

Model Garden offers more than 200 models: Google's Gemini, Imagen, Veo and Chirp models, partner models such as Anthropic's Claude family, and open models such as Gemma and Llama that can be deployed or tuned. Developers prototype prompts in a studio console, ground answers with Google Search or their own data, tune models and evaluate them with the Gen AI evaluation service. RAG Engine connects private data to models, and Vector Search provides a managed vector database. For classic machine learning, Vertex AI still offers custom training on GPUs and TPUs, AutoML, Pipelines, Feature Store, a model registry, monitoring and Colab Enterprise notebooks.

Vertex AI's strengths are first-party access to Gemini, a broad Model Garden including Claude, deep integration with BigQuery and Google Cloud security, a strong open-source agent framework and full MLOps tooling. Its weaknesses are complexity, frequent product renaming, pricing that is hard to forecast and the need for a Google Cloud account and engineering skills. Amazon Bedrock and Azure AI Foundry are the equivalent platforms on AWS and Microsoft Azure. Google AI Studio offers simpler Gemini API access for prototypes. Hugging Face hosts open models, and Databricks suits teams centered on lakehouse data. Choose Vertex AI if your company runs on Google Cloud and needs governed, production AI.