Google Vertex AI is the unified ML and AI platform on Google Cloud, combining traditional AutoML and custom model training with the Gemini API, Model Garden, and agent builder tools introduced in 2024.
**Model Garden**
Vertex AI Model Garden provides access to 150+ foundation models including Gemini, Claude (via Anthropic partnership), Llama, Mistral, and specialised models for specific tasks. Having multiple frontier models under one enterprise contract with unified billing is a significant operational advantage.
**Gemini API on Vertex**
Accessing Gemini models via Vertex AI provides enterprise features not available on Google AI Studio: private networking, VPC Service Controls, CMEK encryption, audit logging, and SLA guarantees. For regulated industries, these are non-negotiable requirements.
**Agent Builder**
Vertex AI Agent Builder enables creating RAG-based and tool-using agents grounded in enterprise data, with built-in connectors to Google Drive, BigQuery, and Cloud Storage.
**AutoML**
Vertex AutoML provides point-and-click model training for structured data, image, text, and video without writing ML code. For business teams needing predictive models without data science resources, AutoML remains a strong option.
**MLOps**
Vertex Pipelines, Model Registry, Feature Store, and Model Monitoring provide complete MLOps infrastructure. The integration with other GCP services (BigQuery, Cloud Storage, Dataflow) is seamless.
**Pricing**
Consumption-based pricing varies by service. Gemini API pricing matches Google AI Studio rates. Custom training is billed by compute hour.
**Verdict**
For GCP-centric enterprises, Vertex AI is the natural home for both ML workloads and generative AI. The breadth of the platform and enterprise compliance features are unmatched in the Google ecosystem.