Gemini Enterprise vs Google Vertex AI: pricing, features and which to choose

Google Cloud launched Gemini Enterprise on 2025-10-09 as a workplace entry point for AI. The product incorporates Agentspace, announced in December 2024, and remains separate from Google Workspace Gemini and Gemini Enterprise Agent Platform. Google’s current homepage markets the workplace experience as Gemini for Business, while subscription documentation continues using Gemini Enterprise terminology. The application supports company-data chat, research, workflow work, and agent access across business applications. It is proprietary software delivered as a Google Cloud service, not a downloadable application. This review covers the workplace application and its editions, rather than the developer-focused Agent Platform or a Google Workspace subscription. The distinction matters because Google says the app and Agent Platform require separate purchases.

Gemini provides one prompt experience across email, documents, code, data, and connected business applications. The homepage says selected sources can be indexed while data remains where it is, with access following each user’s existing permissions. Listed connections include Google Workspace, Microsoft 365, Slack, Confluence, Notion, Jira, GitHub, Salesforce, ServiceNow, BigQuery, HubSpot, and Asana. Features include Deep Research, data insights, no-code Workflow Builder, custom and partner agents, memory for tasks and business knowledge, and secure machines for lengthy jobs. Availability varies by edition and release stage. Its connector catalog spans Google Workspace, Microsoft 365, Slack, Salesforce, Jira, GitHub, ServiceNow, BigQuery, and other business tools, allowing organizations to keep information in its original system while applying existing permissions.

Gemini Enterprise suits organizations seeking a Google Cloud workplace agent with company-data connections, permission-aware access, no-code agent building, and edition-based governance. Microsoft Copilot Studio is a close alternative for Power Platform, Teams, Microsoft data, and Copilot Credit billing. OpenAI ChatGPT Enterprise and Anthropic Claude Enterprise are broader enterprise chat choices, while Amazon Q Business targets AWS-oriented deployments. Gemini Enterprise is less suitable for buyers seeking open-source software, self-hosting, or one published quota covering every edition and feature. Choose it for a Google Cloud workplace agent and connected business work. Its workplace application and Agent Platform require separate purchases, so teams selecting technical agent development must budget for a different Google Cloud service. Choose Agent Platform separately when developers need a technical agent platform rather than the per-seat workplace application.

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.