Google Vertex AIPaid
Google Cloud's unified AI platform — access to Gemini and partner models, plus tools to build, deploy, and govern AI and agents.
AI Infrastructure comparison
Google Vertex AI vs Portkey
Pricing, pros, cons, and ideal use cases — side by side.
PortkeyFreemium
An AI gateway that adds routing, caching, observability, and guardrails to LLM traffic through a single control plane.
At a glance
| Google Vertex AI | Portkey | |
|---|---|---|
| Pricing | PaidUsage-based pricing across model and platform services, billed through Google Cloud. | FreemiumFree developer tier. Paid Pro and Enterprise plans add volume, self-hosting, and governance. |
| Category | AI Infrastructure | AI Infrastructure |
| Ideal for | Enterprises already on Google CloudTeams wanting Gemini under enterprise governanceOrganizations consolidating the AI lifecycle on one platform | Enterprises standardizing LLM access across teamsPlatform teams needing routing and failoverOrgs wanting cost and reliability controls in one place |
Pros & cons
Google Vertex AI
Pros
- Gemini plus a broad Model Garden
- End-to-end build, deploy, evaluate, and govern
- Inside Google Cloud IAM and compliance
- Strong data and analytics integration
Cons
- Large, complex platform surface area
- Most valuable only if you are already on GCP
- Getting value requires real platform investment
Portkey
Pros
- Routing, failover, and caching out of the box
- Built-in observability and cost analytics
- Guardrails enforced at the gateway
- Managed or self-hosted
Cons
- Another vendor in the critical request path
- Overlaps with observability tools you may already run
- Full governance features need a paid plan
Which should you choose?
Portkey is the lighter-weight option (Freemium), while Google Vertex AI sits higher on the pricing ladder (Paid). Google Vertex AI is built around enterprises already on google cloud; Portkey leans more toward enterprises standardizing llm access across teams. Shortlist the one whose strengths line up with your biggest constraint.